Data Engineer, Applications Engineering & Manufacturing

What to Expect

This role designs, builds, and maintains the data infrastructure, reports, and applications that power operational decision-making at a manufacturing site. This role partners closely with the Production teams to deliver reliable data pipelines, automate manual workflows, and build reporting and applications that track operational KPIs, surface bottlenecks, and support cost and efficiency decisions on the production floor. The role will own end-to-end analytics solutions—from data ingestion and modeling through dashboards, automation, and ad hoc analysis—that help the site run more efficiently and make faster, better-informed decisions.

What You’ll Do

• Build reliable data pipelines that ingest, transform, and serve manufacturing data
• Create reports/dashboards tracking core operational KPIs that drive action
• Design and maintain dimensional data models (star/snowflake schemas) so operational KPIs are consistent, well-documented, and trusted across and sites
• Build custom applications and automation, including AI-assisted tools, that streamline day-to-day operations
• Deliver ad hoc data analytical solutions to address urgent operational issues
• Collaborate on-site with process owners to understand real workflows and translate operational needs into scalable data solutions
• Ensure data quality, consistency, and documentation so metrics are trusted across sites
• Define, enforce, and continuously improve engineering standards, coding best practices, testing methodologies, CI/CD patterns, monitoring & alerting, and quality assurance processes

What You’ll Bring

• 4+ years of professional experience as a data engineer or in a similar analytics/data engineering role
• Experience building and maintaining ETL/ELT data pipelines that ingest, transform, and serve data reliably in production
• Proficient with SQL and Python for data engineering (pandas, SQLAlchemy, etc.)
• Strong Proficiency with database systems like SQL Server, MySQL, Clickhouse, etc. is required
• Experience designing and operating Airflow DAGs in production at scale
• Experience building dashboards and operational reporting (e.g., Tableau, PowerBI, or equivalent)
• Ability to translate operational problems into practical data solutions and communicate effectively with non-technical stakeholders
• Comfortable working in a fast-paced manufacturing environment with a strong on-site partnership mindset