Warehouse/Shipping Plant Operator

Tessenderlo Group is a diversified industrial group that focuses on agriculture, valorizing bio-residuals and providing industrial solutions. The Group's activities are subdivided into three operating segments: Agro, Bio-Valorization and Industrial Solutions. - Agro: This segment is active in the production and marketing of crop nutrients (liquid crop fertilizers and SOP, sulfate of potash) and crop protection products.- Bio-Valorization: This segment combines the Group's activities in animal by-product processing and it includes Akiolis (rendering, production and sale of proteins and fats) and PB Gelatins (production and sale of gelatins).- Industrial Solutions: This segment covers activities offering products and solutions to industrial end-markets. It includes in essence the production and sale of plastic pipe systems (PPS), water treatment chemicals and other industrial activities, such as the production and sale of mining and industrial chemicals, and the delivery of services for the treatment and disposal of fracking water (ECS), as well as services that enable the on-site optimization of environmental control systems (MPR). The group employs about 4,900 people and is a leader in most of its markets, with a consolidated revenue of 1.5 billion EUR in 2015. Tessenderlo Group is listed on Euronext Brussels and is part of Next 150 and BEL Mid indices. You can find more information on www.tessenderlo.com

The role involves various positions in shipping and warehouse operations, including batch makers, plant operators, and logistics coordinators. Positions are available for both day and night shifts.

The role involves various positions in shipping and warehouse operations, including batch makers, plant operators, and logistics coordinators.

Shipping Warehouse Operations – Day Shift

The role involves various positions in shipping and warehouse operations, including batch makers, plant operators, and logistics coordinators. Positions are available for both day and night shifts.

Tessenderlo

Shipping Warehouse Operations – Day Shift The role involves various positions in shipping and warehouse operations, including batch makers, plant operators, and logistics coordinators. The role involves various positions in shipping and warehouse operations, including batch makers, plant operators, and logistics coordinators. Positions are available for both day and night shifts. Warehouse/Shipping Plant Operator Operations Tessenderlo agricultural-chemical-manufacturing agriculture-construction-mining-machinery-manufacturing chemical-manufacturing industrial-machinery-manufacturing mechanical-engineering electronic-and-precision-equipment-maintenance water-waste-steam-and-air-conditioning-services energy biotechnology-research chemical chemicals collecting manufacturing medical pharmaceutical-manufacturing pharmaceuticals water-management-systems water-treatment-chemicals

Various Positions

Tessenderlo Group is hiring for various positions including HSE Specialist, Maintenance Technician, Logistics Coordinator, and more across different locations. The roles span across different departments such as Operations, Accounting, and Engineering, with opportunities available in Phoenix, AZ, Fresno, CA, and Irricana, Canada.

Tessenderlo Group is hiring for various positions including HSE Specialist, Maintenance Technician, Logistics Coordinator, and more across different locations.

Careers at Tessenderlo Group - SmartRecruiters

United States

Tessenderlo Group is hiring for various positions including HSE Specialist, Maintenance Technician, Logistics Coordinator, and more across different locations. The roles span across different departments such as Operations, Accounting, and Engineering, with opportunities available in Phoenix, AZ, Fresno, CA, and Irricana, Canada.

Careers at Tessenderlo Group - SmartRecruiters Tessenderlo Group is hiring for various positions including HSE Specialist, Maintenance Technician, Logistics Coordinator, and more across different locations. Tessenderlo Group is hiring for various positions including HSE Specialist, Maintenance Technician, Logistics Coordinator, and more across different locations. The roles span across different departments such as Operations, Accounting, and Engineering, with opportunities available in Phoenix, AZ, Fresno, CA, and Irricana, Canada. Various Positions Operations Tessenderlo agricultural-chemical-manufacturing agriculture-construction-mining-machinery-manufacturing chemical-manufacturing industrial-machinery-manufacturing mechanical-engineering electronic-and-precision-equipment-maintenance water-waste-steam-and-air-conditioning-services energy biotechnology-research chemical chemicals collecting manufacturing medical pharmaceutical-manufacturing pharmaceuticals water-management-systems water-treatment-chemicals Arizona California

Tessenderlo Group offers a range of career opportunities in fields such as health, safety, environment, maintenance, logistics, and accounting. Positions are available in multiple locations including Phoenix, AZ, Fresno, CA, and Irricana, Canada.

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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