Assoc. Dir , Data Engineering

About Us

The Manufacturing Value Team is a strategic arm of the Digital Manufacturing Division, focused on delivering digital solutions that drive operational excellence, compliance, and innovation across global manufacturing sites. We combine deep business process knowledge with cutting‑edge technology to support factory automation, data analytics, and system lifecycle management. Our mission is to enable smarter, faster, and more compliant manufacturing through digital transformation.

The Associate Director, Data Engineering, is part of the Launch Line Intelligence product line team. The incumbent provides technical leadership for manufacturing and process analytics data engineering capabilities. This role is accountable for delivering high‑quality, reliable, and governed data products that enable Manufacturing Science & Technology and Commercialization customers to run Proactive Process Analytics (PPA), batch data investigations, and cross‑site process robustness using a variety of in‑house‑built or COTS solutions.

The role operates at the enterprise level, partnering with Technical Product Managers, Tech Ops customers, and process data Subject Matter Experts, solution architects, data scientists, data analysts, and cross‑divisional IT teams to translate data strategy into scalable, reusable, and compliant data engineering solutions.

• Understand the manufacturing process, process data generation, process data consumption, and analytics usage, and then lead the design, build, and operation of end‑to‑end data pipelines (ingest > transform > publish) using SQL, Python, and dbt, ensuring reliability, freshness, observability, and performance. Build a data strategy to ingest data from both structured and standardized data source systems (e.g., SAP, MES, LIMS) as well as from spreadsheets, paper documents, or other file‑based systems.
  
  Build and own data integrity specifications, and incorporate controls into IT solutions to enforce data quality and integrity. Advice on data transformation, context of how data shall be stored, retrieved, and used.
• Collaborate with internal site process SMEs across R&D, CMC, Internal and External manufacturing process SMEs, Digital Services data engineering and data lake teams, manufacturing application software development teams, Suppliers (e.g. Seeq)
• Establish and enforce data engineering standards, reusable pipeline patterns, and data modeling conventions (star/snowflake) aligned with Manufacturing Process Intelligence solution governance.
• Ensure compliance with SDLC, documentation, testing, deployment, and run book expectations, including GMP/GxP data usage considerations.
• Define and monitor SLAs, data quality thresholds, and freshness metrics for prioritized data products.
• Partner with Technical Product Managers and stakeholders to refine backlogs, prioritize investments, and balance speed, quality, and scalability.
• Mentor and develop data engineers, fostering strong engineering fundamentals, domain understanding, and consistent ways of working.
• Champion data literacy through trainings, office hours, templates, and job aides to enable governed self‑service analytics.

• Bachelor’s degree in engineering, Computer Science, or a related field. And a minimum 8‑10 years of relevant experience in this field.
• Strong expertise in SQL and data modeling with working knowledge of Python.
• Experience designing and operating ETL/ELT pipelines, orchestration, and data quality monitoring. Understanding of data lakes, data marts, data ingestion patterns,
• Hands on experience with relational schema design, data warehousing concepts, and performance optimization.
• Knowledge of biopharmaceutical manufacturing processes, generated process data, discrete and time‑series data, manufacturing systems (e.g. MES, LIMS, PI, SAP) that generate the data, and scientific Tech Ops processes that consume the data – e.g. deviation and batch discard investigations, continuous process verification, statistical process control charts, AI/ML workloads (e.g. random forests, PCA).

• Experience with MANTIS Data lake (connections,…