Senior AI Engineer

Prompt Praxis Laboratories, LLC, founded in 2011, is a women-owned fully-integrated laboratory powered with the current information technology to facilitate rapid drug testing or development. The emphasis on automation of critical laboratory processes allows PPL to minimize human error within the testing and analysis process. Prompt Praxis Laboratories provides a full range of rapid testing and support services focusing on pharmaceutical products and compounded sterile or nonsterile preparations. Our support activities span three major industries:> Pharmaceutical> Compounding Pharmacy> Medical DevicesThe scope and breath of the services we offer are extensive, and we anticipate phasing in specialty capabilities based upon the growth of our client base and diversification of development activities. Services in support of other dosage forms may be included in various expansion phases of the laboratory. Prompt Praxis Laboratories, LLC, has developed and validated numerous Ready-to-Analyze® test methods. These methods have been validated to a typical concentration range of 1 to 50 µg/mL with short run times facilitating rapid turnaround. These methods are envisioned to be applicable without further validation to test samples after a quick specificity experiment that demonstrates their utility on the specific samples to be tested. We hope to encourage compliance with the new 503B section of the Food, Drug & Cosmetic Act by cost-effectively providing options to physicians, pharmacies, and outsourcing facilities in an effort to ensure chemically safe and effective compounded preparations.

Prompt is a mission-driven startup looking for an experienced Senior AI Engineer to help push forward an ambitious set of AI initiatives in healthcare, with a particular emphasis on speech and language processing. The role involves designing, building, and deploying AI systems, partnering with stakeholders, and developing internal AI tools to enhance efficiency and decision-making. Responsibilities include leading AI projects from ideation to production, designing evaluation and monitoring metrics, building guardrails around LLM pipelines, developing prototypes, and mentoring team members. The ideal candidate has over 4 years of experience in AI/ML, strong software engineering skills, expertise with LLM-based systems, and familiarity with cloud platforms like AWS. Perks include competitive salary, remote/hybrid work, equity potential, health benefits, and wellness programs.

Prompt is seeking a Senior AI Engineer to develop and deploy AI systems in healthcare, focusing on speech and language processing.

United States

Prompt is a mission-driven startup looking for an experienced Senior AI Engineer to help push forward an ambitious set of AI initiatives in healthcare, with a particular emphasis on speech and language processing. The role involves designing, building, and deploying AI systems, partnering with stakeholders, and developing internal AI tools to enhance efficiency and decision-making. Responsibilities include leading AI projects from ideation to production, designing evaluation and monitoring metrics, building guardrails around LLM pipelines, developing prototypes, and mentoring team members. The ideal candidate has over 4 years of experience in AI/ML, strong software engineering skills, expertise with LLM-based systems, and familiarity with cloud platforms like AWS. Perks include competitive salary, remote/hybrid work, equity potential, health benefits, and wellness programs.Requirements:<ul><li> 4+ years of experience building AI/ML systems in industry or academia, with meaningful production ownership</li><li> Strong experience building and operating AI systems end-to-end, not just models in isolation</li><li> Strong experience with LLM-based systems (programmatic prompt optimization, evaluation, prompting, structured outputs, RAG, multi-step workflows)</li><li> Solid understanding of evaluation and measurement for AI systems (offline metrics, online monitoring, regressions, cost tracking)</li><li> Ability to work closely with non-technical stakeholders to translate workflows into effective AI solutions</li><li> Strong software engineering fundamentals and ability to ship maintainable, production-grade systems</li><li> Track record of benchmarking and iteratively improving accuracy, cost, and latency</li><li> Excellent communication skills, with the ability to explain complex AI concepts to non-technical stakeholders</li><li> Proficiency in Python (>3.9)</li><li> Basic knowledge of Docker</li><li> Familiarity with AWS services (S3, RDS, EC2) preferred</li><li> Strong problem-solving mindset and ability to operate effectively in ambiguous, fast-paced settings</li><li> Willingness to learn and understand healthcare sectors like physical therapy, occupational therapy, and speech therapy</li><li> Interest in heavy code contribution roles; not suitable for engineering management positions</li></ul>Benefits:<ul><li> Competitive salaries</li><li> Remote/hybrid environment</li><li> Potential equity compensation for outstanding performance</li><li> Flexible PTO</li><li> Company-wide sponsored lunches</li><li> Company paid disability and life insurance benefits</li><li> Company paid family and medical leave</li><li> Medical, dental, and vision insurance benefits</li><li> Discounted pet insurance</li><li> FSA/DCA and commuter benefits</li><li> 401k</li><li> Credits for online fitness classes/gym memberships</li><li> Recovery suite at HQ – includes a cold plunge, sauna, and shower</li></ul>

Prompt Praxis Labs

Senior AI Engineer Prompt is seeking a Senior AI Engineer to develop and deploy AI systems in healthcare, focusing on speech and language processing. Prompt is a mission-driven startup looking for an experienced Senior AI Engineer to help push forward an ambitious set of AI initiatives in healthcare, with a particular emphasis on speech and language processing. The role involves designing, building, and deploying AI systems, partnering with stakeholders, and developing internal AI tools to enhance efficiency and decision-making. Responsibilities include leading AI projects from ideation to production, designing evaluation and monitoring metrics, building guardrails around LLM pipelines, developing prototypes, and mentoring team members. The ideal candidate has over 4 years of experience in AI/ML, strong software engineering skills, expertise with LLM-based systems, and familiarity with cloud platforms like AWS. Perks include competitive salary, remote/hybrid work, equity potential, health benefits, and wellness programs. Senior AI Engineer AI Engineer Prompt Praxis Labs chemicals allied-products analytical-development analytical-testing compatibility-testing compounding compounding-pharmacy formulation-development health-care hospital medical medical-devices nec pharmaceutical pharmaceutical-services pharmaceuticals

The role involves designing, evaluating, and monitoring AI systems, collaborating with stakeholders, and leading AI projects to improve healthcare technology. It requires building end-to-end AI solutions and contributing to internal tools and product AI initiatives.

AI Engineer

Prompt is a mission-driven startup looking for an experienced Senior AI Engineer to help push forward an ambitious set of AI initiatives in healthcare, with a particular emphasis on speech and language processing. The role involves leading AI projects from ideation to deployment, developing real-time AI systems involving speech and natural language understanding, and applying AI to improve clinical documentation, customer support, and billing workflows. The engineer will collaborate with product and engineering teams, develop deep understanding of healthcare applications, and help grow and lead the AI team. The position requires building and evaluating NLP and speech pipelines, benchmarking models, and working with modern AI tools and cloud platforms. The company offers a remote/hybrid environment, competitive salary, equity potential, and comprehensive benefits.

Prompt is seeking a Senior AI Engineer to develop real-time speech and language processing AI systems in healthcare.

Senior AI Engineer (Natural Language Systems)

Prompt is a mission-driven startup looking for an experienced Senior AI Engineer to help push forward an ambitious set of AI initiatives in healthcare, with a particular emphasis on speech and language processing. The role involves leading AI projects from ideation to deployment, developing real-time AI systems involving speech and natural language understanding, and applying AI to improve clinical documentation, customer support, and billing workflows. The engineer will collaborate with product and engineering teams, develop deep understanding of healthcare applications, and help grow and lead the AI team. The position requires building and evaluating NLP and speech pipelines, benchmarking models, and working with modern AI tools and cloud platforms. The company offers a remote/hybrid environment, competitive salary, equity potential, and comprehensive benefits.Requirements:<ul><li> 4+ years of experience building AI/ML systems in industry or academia, with meaningful production ownership</li><li> Strong experience building and evaluating NLP and/or LLM systems (e.g., retrieval, summarization, classification, extraction, agent workflows)</li><li> Experience working with speech-related pipelines in production or near-real-time settings (e.g., speech-to-text, spoken intent classification, conversational AI)</li><li> Track record of benchmarking and iteratively improving accuracy, cost, and latency</li><li> Enthusiastic and pragmatic problem-solving mindset</li><li> Excellent communication skills, with the ability to explain complex AI concepts to non-technical stakeholders</li><li> Python (>3.9)</li><li> Docker (Basics)</li><li> AWS familiarity (S3, RDS, EC2) preferred</li><li> Willingness to learn and deeply understand the healthcare sector, specifically physical therapy, occupational therapy, and speech therapy</li><li> Please only apply if you are interested in a heavy code contribution role; this is not an engineering management position, though growth opportunities exist over time</li></ul>Benefits:<ul><li> Competitive salaries</li><li> Remote/hybrid environment</li><li> Potential equity compensation for outstanding performance</li><li> Flexible PTO</li><li> Company-wide sponsored lunches</li><li> Company paid disability and life insurance benefits</li><li> Company paid family and medical leave</li><li> Medical, dental, and vision insurance benefits</li><li> Discounted pet insurance</li><li> FSA/DCA and commuter benefits</li><li> 401k</li><li> Credits for online fitness classes/gym memberships</li><li> Recovery suite at HQ – includes a cold plunge, sauna, and shower</li></ul>

Senior AI Engineer (Natural Language Systems) Prompt is seeking a Senior AI Engineer to develop real-time speech and language processing AI systems in healthcare. Prompt is a mission-driven startup looking for an experienced Senior AI Engineer to help push forward an ambitious set of AI initiatives in healthcare, with a particular emphasis on speech and language processing. The role involves leading AI projects from ideation to deployment, developing real-time AI systems involving speech and natural language understanding, and applying AI to improve clinical documentation, customer support, and billing workflows. The engineer will collaborate with product and engineering teams, develop deep understanding of healthcare applications, and help grow and lead the AI team. The position requires building and evaluating NLP and speech pipelines, benchmarking models, and working with modern AI tools and cloud platforms. The company offers a remote/hybrid environment, competitive salary, equity potential, and comprehensive benefits. AI Engineer AI Engineer Prompt Praxis Labs chemicals allied-products analytical-development analytical-testing compatibility-testing compounding compounding-pharmacy formulation-development health-care hospital medical medical-devices nec pharmaceutical pharmaceutical-services pharmaceuticals

This role involves leading AI projects in healthcare, focusing on speech and NLP, and building reliable, production-grade systems. The engineer will work on real-world workflows, improve AI models, and contribute to strategic AI roadmaps.

IT Data Engineer

The Dow Chemical Company, commonly known as Dow, is a global leader in materials science, specializing in the production of chemicals, plastics, and agricultural products. Founded in 1897, Dow develops innovative solutions that help address many of the world's most pressing challenges in packaging, infrastructure, and consumer care. The company operates worldwide, serving diverse industries with a commitment to sustainability and advancing the circular economy. Dow's extensive portfolio includes performance materials, industrial intermediates, and specialty chemicals, making it a key player in the global chemical manufacturing sector.

At Dow, we believe in putting people first and we’re passionate about delivering integrity, respect and safety to our customers, our employees and the planet. Our people are at the heart of our solutions. They reflect the communities we live in and the world where we do business. Their diversity is our strength. We’re a community of relentless problem solvers that offers the daily opportunity to contribute with your perspective, transform industries and shape the future. Our purpose is simple - to deliver a sustainable future for the world through science and collaboration. If you’re looking for a challenge and meaningful role, you’re in the right place. Dow (NYSE: DOW) is one of the world’s leading materials science companies, serving customers in high-growth markets such as packaging, infrastructure, mobility and consumer applications. Our global breadth, asset integration and scale, focused innovation, leading business positions and commitment to sustainability enable us to achieve profitable growth and help deliver a sustainable future. We operate manufacturing sites in 30 countries and employ approximately 36,000 people. Dow delivered sales of approximately $43 billion in 2024. References to Dow or the Company mean Dow Inc. and its subsidiaries. Learn more about us and our ambition to be the most innovative, customer-centric, inclusive and sustainable materials science company in the world by visiting www.dow.com. About you and this role Dow has an exciting opportunity for a Data Engineer located in Midland, MI or Houston, TX. This role will make significant technical contributions to critical data initiatives within our team at Dow. You will be responsible for driving the technical implementation and contributing to the design of scalable, Gold-layer data products on the Azure Databricks Lakehouse Platform. This role focuses on solving complex technical challenges, optimization, architecture contribution, and reliability, ensuring our datasets are performant and ready to power advanced use cases, including: Machine Learning (ML) Pipelines Real-Time Data Consumption Generative and Agentic AI Systems Core Enterprise Reporting and BI Data-driven Applications Responsibilities Technical Design Contribution: Collaborate with senior data engineers to translate complex business requirements and ambiguous problem statements into clear, robust, and scalable technical designs and data models (e.g., dimensional modeling, star schemas), and independently drive the implementation of these designs. Performance Optimization: Design, build, and deploy high-volume data transformation logic using highly optimized PySpark. You will apply advanced techniques to tune Spark jobs and diagnose performance bottlenecks to ensure maximum efficiency and minimal cloud compute cost. Architecture & Deployment: Contribute significantly to the design and improvement of CI/CD pipelines in Azure DevOps/Git, ensuring reliable, automated, and secure deployment of data solutions across environments. Diverse Data Integration: Deeply understand and connect to various source systems, demonstrating proficiency in managing data persistence and query performance across diverse technologies like SQL Server, Neo4j, and CosmosDB. Quality & Governance: Proactively implement and maintain advanced data quality frameworks (e.g., Delta Live Tables, Great Expectations) and monitoring solutions to ensure data reliability for mission-critical applications. Collaboration & Mentorship: Serve as a go-to technical resource for peers, conducting technical code reviews and informally mentoring Associate Data Engineers on PySpark and Databricks best practices. A successful candidate will possess the experience and technical depth required to independently implement and optimize complex data solutions: Core Technical Expertise (2-5 Years Demonstrated Experience) PySpark and Distributed Processing: Proven ability to write highly optimized, production-grade PySpark/Spark code. Experience identifying and resolving performance bottlenecks in a distributed computing environment. Advanced Data Modeling: Practical experience designing and implementing analytical data models (e.g., dimensional modeling, star/snowflake schemas) and handling Slowly Changing Dimensions (SCDs). Cloud Orchestration: Expertise in using Azure Data Factory (ADF), Databricks Workflows, or equivalent tools (e.g., Airflow) for complex dependency management, error handling, and end-to-end pipeline orchestration. Database Versatility: Demonstrated experience with advanced SQL and hands-on experience querying and integrating data from at least one non-relational or Graph database (e.g., CosmosDB, Neo4j). Engineering Mindset and Professional Growth Technical Design Contribution: Ability to rapidly synthesize information and contribute clear, well-documented technical specifications and architectural diagrams to the design process. Feature Ownership: Demonstrated history of taking ownership of complex features and modules within larger projects, driving them to completion, and managing technical dependencies autonomously. Pragmatism and Initiative: A strong bias for action, coupled with a pragmatic approach to delivering stable, maintainable, and cost-effective solutions. Communication & Influence: Excellent verbal and written communication skills, with the ability to articulate technical designs to both engineering peers and senior stakeholders, effectively influencing technical decisions. Required Qualifications A minimum of a bachelor’s degree or relevant military experience at or above a U.S. E5 ranking or Canadian Petty Officer 2nd Class or Sergeant OR 5 years relevant experience in lieu of a Bachelor’s degree. Minimum of 2 years of professional experience in Data Engineering, Software Engineering, or a closely related field. A minimum requirement for this U.S. based position is the ability to work legally in the United States. No visa sponsorship/support is available for this position, including for any type of U.S. permanent residency (green card) process. Preferred Skills Experience with cloud cost management principles related to compute (Databricks) and storage (ADLS). Experience with Infrastructure as Code (e.g., Terraform, ARM templates). Proficiency with data visualization and dashboarding tools (e.g., Power BI, Tableau). Your Skills PySpark / Distributed Data Processing: The ability to build, optimize, and troubleshoot high‑volume data transformation pipelines using PySpark, including tuning Spark jobs, resolving performance bottlenecks, and ensuring efficient distributed execution. Advanced Data Modeling (Dimensional / Star Schema Design): Expertise in translating complex business requirements into scalable analytical data models—such as star and snowflake schemas—and implementing SCD logic for downstream analytics. Cloud Orchestration & CI/CD (Azure Data Factory, Databricks Workflows, Azure DevOps/Git): Skill in designing automated, reliable data pipelines, managing task dependencies, and implementing CI/CD deployment processes across environments. Data Integration Across Diverse Systems (SQL Server, CosmosDB, Neo4j): Ability to connect to, query, and integrate data from relational and non‑relational sources while optimizing persistence, ingestion, and query performance. Data Quality Engineering & Governance (Delta Live Tables, Great Expectations): Applying validation frameworks, monitoring, and automated quality checks to ensure data reliability for ML, real‑time analytics, and enterprise BI use cases. Note: relocation assistance is not provided with this role.

Dow is seeking a Data Engineer to develop scalable data solutions on Azure Databricks, focusing on performance, architecture, and data quality.

At Dow, we believe in putting people first and we’re passionate about delivering integrity, respect and safety to our customers, our employees and the planet. Our people are at the heart of our solutions. They reflect the communities we live in and the world where we do business. Their diversity is our strength. We’re a community of relentless problem solvers that offers the daily opportunity to contribute with your perspective, transform industries and shape the future. Our purpose is simple - to deliver a sustainable future for the world through science and collaboration. If you’re looking for a challenge and meaningful role, you’re in the right place. Dow (NYSE: DOW) is one of the world’s leading materials science companies, serving customers in high-growth markets such as packaging, infrastructure, mobility and consumer applications. Our global breadth, asset integration and scale, focused innovation, leading business positions and commitment to sustainability enable us to achieve profitable growth and help deliver a sustainable future. We operate manufacturing sites in 30 countries and employ approximately 36,000 people. Dow delivered sales of approximately $43 billion in 2024. References to Dow or the Company mean Dow Inc. and its subsidiaries. Learn more about us and our ambition to be the most innovative, customer-centric, inclusive and sustainable materials science company in the world by visiting www.dow.com. About you and this role Dow has an exciting opportunity for a Data Engineer located in Midland, MI or Houston, TX. This role will make significant technical contributions to critical data initiatives within our team at Dow. You will be responsible for driving the technical implementation and contributing to the design of scalable, Gold-layer data products on the Azure Databricks Lakehouse Platform. This role focuses on solving complex technical challenges, optimization, architecture contribution, and reliability, ensuring our datasets are performant and ready to power advanced use cases, including: Machine Learning (ML) Pipelines Real-Time Data Consumption Generative and Agentic AI Systems Core Enterprise Reporting and BI Data-driven Applications Responsibilities Technical Design Contribution: Collaborate with senior data engineers to translate complex business requirements and ambiguous problem statements into clear, robust, and scalable technical designs and data models (e.g., dimensional modeling, star schemas), and independently drive the implementation of these designs. Performance Optimization: Design, build, and deploy high-volume data transformation logic using highly optimized PySpark. You will apply advanced techniques to tune Spark jobs and diagnose performance bottlenecks to ensure maximum efficiency and minimal cloud compute cost. Architecture & Deployment: Contribute significantly to the design and improvement of CI/CD pipelines in Azure DevOps/Git, ensuring reliable, automated, and secure deployment of data solutions across environments. Diverse Data Integration: Deeply understand and connect to various source systems, demonstrating proficiency in managing data persistence and query performance across diverse technologies like SQL Server, Neo4j, and CosmosDB. Quality & Governance: Proactively implement and maintain advanced data quality frameworks (e.g., Delta Live Tables, Great Expectations) and monitoring solutions to ensure data reliability for mission-critical applications. Collaboration & Mentorship: Serve as a go-to technical resource for peers, conducting technical code reviews and informally mentoring Associate Data Engineers on PySpark and Databricks best practices. A successful candidate will possess the experience and technical depth required to independently implement and optimize complex data solutions: Core Technical Expertise (2-5 Years Demonstrated Experience) PySpark and Distributed Processing: Proven ability to write highly optimized, production-grade PySpark/Spark code. Experience identifying and resolving performance bottlenecks in a distributed computing environment. Advanced Data Modeling: Practical experience designing and implementing analytical data models (e.g., dimensional modeling, star/snowflake schemas) and handling Slowly Changing Dimensions (SCDs). Cloud Orchestration: Expertise in using Azure Data Factory (ADF), Databricks Workflows, or equivalent tools (e.g., Airflow) for complex dependency management, error handling, and end-to-end pipeline orchestration. Database Versatility: Demonstrated experience with advanced SQL and hands-on experience querying and integrating data from at least one non-relational or Graph database (e.g., CosmosDB, Neo4j). Engineering Mindset and Professional Growth Technical Design Contribution: Ability to rapidly synthesize information and contribute clear, well-documented technical specifications and architectural diagrams to the design process. Feature Ownership: Demonstrated history of taking ownership of complex features and modules within larger projects, driving them to completion, and managing technical dependencies autonomously. Pragmatism and Initiative: A strong bias for action, coupled with a pragmatic approach to delivering stable, maintainable, and cost-effective solutions. Communication & Influence: Excellent verbal and written communication skills, with the ability to articulate technical designs to both engineering peers and senior stakeholders, effectively influencing technical decisions. Required Qualifications A minimum of a bachelor’s degree or relevant military experience at or above a U.S. E5 ranking or Canadian Petty Officer 2nd Class or Sergeant OR 5 years relevant experience in lieu of a Bachelor’s degree. Minimum of 2 years of professional experience in Data Engineering, Software Engineering, or a closely related field. A minimum requirement for this U.S. based position is the ability to work legally in the United States. No visa sponsorship/support is available for this position, including for any type of U.S. permanent residency (green card) process. Preferred Skills Experience with cloud cost management principles related to compute (Databricks) and storage (ADLS). Experience with Infrastructure as Code (e.g., Terraform, ARM templates). Proficiency with data visualization and dashboarding tools (e.g., Power BI, Tableau). Your Skills PySpark / Distributed Data Processing: The ability to build, optimize, and troubleshoot high‑volume data transformation pipelines using PySpark, including tuning Spark jobs, resolving performance bottlenecks, and ensuring efficient distributed execution. Advanced Data Modeling (Dimensional / Star Schema Design): Expertise in translating complex business requirements into scalable analytical data models—such as star and snowflake schemas—and implementing SCD logic for downstream analytics. Cloud Orchestration & CI/CD (Azure Data Factory, Databricks Workflows, Azure DevOps/Git): Skill in designing automated, reliable data pipelines, managing task dependencies, and implementing CI/CD deployment processes across environments. Data Integration Across Diverse Systems (SQL Server, CosmosDB, Neo4j): Ability to connect to, query, and integrate data from relational and non‑relational sources while optimizing persistence, ingestion, and query performance. Data Quality Engineering & Governance (Delta Live Tables, Great Expectations): Applying validation frameworks, monitoring, and automated quality checks to ensure data reliability for ML, real‑time analytics, and enterprise BI use cases. Note: relocation assistance is not provided with this role.Benefits:<ul><li> Equitable and market-competitive base pay and bonus opportunity across our global markets, along with locally relevant incentives.</li><li> Benefits and programs to support your physical, mental, financial, and social well-being, to help you get the care you need...when you need it.</li><li> Competitive retirement program that may include company-provided benefits, savings opportunities, financial planning, and educational resources to help you achieve your long term financial-goals.</li><li> Employee stock purchase programs (availability varies depending on location).</li><li> Student Debt Retirement Savings Match Program (U.S. only).</li><li> Robust medical and life insurance packages that offer a variety of coverage options to meet your individual needs.</li><li> Travel insurance is also available in certain countries/locations.</li><li> Opportunities to learn and grow through training and mentoring, work experiences, community involvement and team building.</li><li> Workplace culture empowering role-based flexibility to maximize personal productivity and balance personal needs.</li><li> Competitive yearly vacation allowance.</li><li> Paid time off for new parents (birthing and non-birthing, including adoptive and foster parents).</li><li> Paid time off to care for family members who are sick or injured.</li><li> Paid time off to support volunteering and Employee Resource Group’s (ERG) participation.</li><li> Wellbeing Portal for all Dow employees, our one-stop shop to promote wellbeing, empowering employees to take ownership of their entire wellbeing journey.</li><li> On-site fitness facilities to help stay healthy and active (availability varies depending on location).</li><li> Employee discounts for online shopping, cinema tickets, gym memberships and more.</li></ul>

The Dow Chemical Company

IT Data Engineer Dow is seeking a Data Engineer to develop scalable data solutions on Azure Databricks, focusing on performance, architecture, and data quality. At Dow, we believe in putting people first and we’re passionate about delivering integrity, respect and safety to our customers, our employees and the planet. Our people are at the heart of our solutions. They reflect the communities we live in and the world where we do business. Their diversity is our strength. We’re a community of relentless problem solvers that offers the daily opportunity to contribute with your perspective, transform industries and shape the future. Our purpose is simple - to deliver a sustainable future for the world through science and collaboration. If you’re looking for a challenge and meaningful role, you’re in the right place. Dow (NYSE: DOW) is one of the world’s leading materials science companies, serving customers in high-growth markets such as packaging, infrastructure, mobility and consumer applications. Our global breadth, asset integration and scale, focused innovation, leading business positions and commitment to sustainability enable us to achieve profitable growth and help deliver a sustainable future. We operate manufacturing sites in 30 countries and employ approximately 36,000 people. Dow delivered sales of approximately $43 billion in 2024. References to Dow or the Company mean Dow Inc. and its subsidiaries. Learn more about us and our ambition to be the most innovative, customer-centric, inclusive and sustainable materials science company in the world by visiting www.dow.com. About you and this role Dow has an exciting opportunity for a Data Engineer located in Midland, MI or Houston, TX. This role will make significant technical contributions to critical data initiatives within our team at Dow. You will be responsible for driving the technical implementation and contributing to the design of scalable, Gold-layer data products on the Azure Databricks Lakehouse Platform. This role focuses on solving complex technical challenges, optimization, architecture contribution, and reliability, ensuring our datasets are performant and ready to power advanced use cases, including: Machine Learning (ML) Pipelines Real-Time Data Consumption Generative and Agentic AI Systems Core Enterprise Reporting and BI Data-driven Applications Responsibilities Technical Design Contribution: Collaborate with senior data engineers to translate complex business requirements and ambiguous problem statements into clear, robust, and scalable technical designs and data models (e.g., dimensional modeling, star schemas), and independently drive the implementation of these designs. Performance Optimization: Design, build, and deploy high-volume data transformation logic using highly optimized PySpark. You will apply advanced techniques to tune Spark jobs and diagnose performance bottlenecks to ensure maximum efficiency and minimal cloud compute cost. Architecture & Deployment: Contribute significantly to the design and improvement of CI/CD pipelines in Azure DevOps/Git, ensuring reliable, automated, and secure deployment of data solutions across environments. Diverse Data Integration: Deeply understand and connect to various source systems, demonstrating proficiency in managing data persistence and query performance across diverse technologies like SQL Server, Neo4j, and CosmosDB. Quality & Governance: Proactively implement and maintain advanced data quality frameworks (e.g., Delta Live Tables, Great Expectations) and monitoring solutions to ensure data reliability for mission-critical applications. Collaboration & Mentorship: Serve as a go-to technical resource for peers, conducting technical code reviews and informally mentoring Associate Data Engineers on PySpark and Databricks best practices. A successful candidate will possess the experience and technical depth required to independently implement and optimize complex data solutions: Core Technical Expertise (2-5 Years Demonstrated Experience) PySpark and Distributed Processing: Proven ability to write highly optimized, production-grade PySpark/Spark code. Experience identifying and resolving performance bottlenecks in a distributed computing environment. Advanced Data Modeling: Practical experience designing and implementing analytical data models (e.g., dimensional modeling, star/snowflake schemas) and handling Slowly Changing Dimensions (SCDs). Cloud Orchestration: Expertise in using Azure Data Factory (ADF), Databricks Workflows, or equivalent tools (e.g., Airflow) for complex dependency management, error handling, and end-to-end pipeline orchestration. Database Versatility: Demonstrated experience with advanced SQL and hands-on experience querying and integrating data from at least one non-relational or Graph database (e.g., CosmosDB, Neo4j). Engineering Mindset and Professional Growth Technical Design Contribution: Ability to rapidly synthesize information and contribute clear, well-documented technical specifications and architectural diagrams to the design process. Feature Ownership: Demonstrated history of taking ownership of complex features and modules within larger projects, driving them to completion, and managing technical dependencies autonomously. Pragmatism and Initiative: A strong bias for action, coupled with a pragmatic approach to delivering stable, maintainable, and cost-effective solutions. Communication & Influence: Excellent verbal and written communication skills, with the ability to articulate technical designs to both engineering peers and senior stakeholders, effectively influencing technical decisions. Required Qualifications A minimum of a bachelor’s degree or relevant military experience at or above a U.S. E5 ranking or Canadian Petty Officer 2nd Class or Sergeant OR 5 years relevant experience in lieu of a Bachelor’s degree. Minimum of 2 years of professional experience in Data Engineering, Software Engineering, or a closely related field. A minimum requirement for this U.S. based position is the ability to work legally in the United States. No visa sponsorship/support is available for this position, including for any type of U.S. permanent residency (green card) process. Preferred Skills Experience with cloud cost management principles related to compute (Databricks) and storage (ADLS). Experience with Infrastructure as Code (e.g., Terraform, ARM templates). Proficiency with data visualization and dashboarding tools (e.g., Power BI, Tableau). Your Skills PySpark / Distributed Data Processing: The ability to build, optimize, and troubleshoot high‑volume data transformation pipelines using PySpark, including tuning Spark jobs, resolving performance bottlenecks, and ensuring efficient distributed execution. Advanced Data Modeling (Dimensional / Star Schema Design): Expertise in translating complex business requirements into scalable analytical data models—such as star and snowflake schemas—and implementing SCD logic for downstream analytics. Cloud Orchestration & CI/CD (Azure Data Factory, Databricks Workflows, Azure DevOps/Git): Skill in designing automated, reliable data pipelines, managing task dependencies, and implementing CI/CD deployment processes across environments. Data Integration Across Diverse Systems (SQL Server, CosmosDB, Neo4j): Ability to connect to, query, and integrate data from relational and non‑relational sources while optimizing persistence, ingestion, and query performance. Data Quality Engineering & Governance (Delta Live Tables, Great Expectations): Applying validation frameworks, monitoring, and automated quality checks to ensure data reliability for ML, real‑time analytics, and enterprise BI use cases. Note: relocation assistance is not provided with this role. IT Data Engineer Architect The Dow Chemical Company Chemicals Materials Manufacturing Agriculture

This role involves designing and optimizing data pipelines, collaborating on technical designs, and ensuring data reliability for advanced analytics and AI applications. The candidate will work with diverse data systems and contribute to critical data initiatives at Dow.

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