Director, Data Engineering Lead - Digital Insights
Merck
August 12, 2026
Remote friendly (Boston, MA)
United States
IT
Responsibilities:
- Lead, coach, and develop a team of business-side data engineers.
- Establish data engineering standards, development practices, and code quality expectations.
- Manage resource allocation, prioritization, and execution across concurrent initiatives.
- Define and execute Digital Insights data engineering strategy aligned with DDT objectives.
- Design, develop, and maintain scalable, reliable, reusable data pipelines.
- Build domain and cross-domain data products for analytics, visualization, modeling, and AI.
- Implement data quality monitoring, lineage, metadata management, and governance.
- Partner with scientists and product/digital teams to translate workflows into data solutions.
- Accelerate access to scientific data from instruments, ELNs, manufacturing systems, and enterprise platforms.
- Enable self-service access to governed scientific data and insights.
- Support predictive analytics, machine learning, digital twins, and agentic AI solutions.
- Partner with IT to define target-state architectures and align with enterprise standards.
- Communicate effectively to technical and non-technical audiences; influence roadmap decisions.
Qualifications:
- Ph.D. with 6+ years, or M.S. with 8+ years, or B.S. with 10+ years in relevant fields.
- Pharmaceutical/biotech/life sciences/healthcare experience; laboratory/manufacturing/process development or research environment experience.
- Knowledge of scientific data platforms, lab informatics systems, and instrument-generated data.
- Experience in data/software/analytics engineering; leading technical teams and enterprise/scientific data programs.
- Enterprise-scale pipelines/data products; cross-functional initiatives.
- Databricks, cloud data platforms, SQL, Python, modern ETL; data modeling, metadata/ontology/master data; familiarity with data lakes/lakehouses/warehouses/knowledge graphs.
- Understanding of AI/ML data requirements.
Required skills: Cross-functional leadership; data engineering/modeling; digital transformation; lab informatics; predictive analytics; regulatory compliance.
Benefits (if applicable): annual bonus and long-term incentive (if applicable) and comprehensive benefits including medical/dental/vision, retirement (401(k)), paid holidays, vacation, compassionate and sick days.
Application: Apply via https://jobs.merck.com/us/en (or Workday Jobs Hub). Application deadline is stated on the posting.
- Lead, coach, and develop a team of business-side data engineers.
- Establish data engineering standards, development practices, and code quality expectations.
- Manage resource allocation, prioritization, and execution across concurrent initiatives.
- Define and execute Digital Insights data engineering strategy aligned with DDT objectives.
- Design, develop, and maintain scalable, reliable, reusable data pipelines.
- Build domain and cross-domain data products for analytics, visualization, modeling, and AI.
- Implement data quality monitoring, lineage, metadata management, and governance.
- Partner with scientists and product/digital teams to translate workflows into data solutions.
- Accelerate access to scientific data from instruments, ELNs, manufacturing systems, and enterprise platforms.
- Enable self-service access to governed scientific data and insights.
- Support predictive analytics, machine learning, digital twins, and agentic AI solutions.
- Partner with IT to define target-state architectures and align with enterprise standards.
- Communicate effectively to technical and non-technical audiences; influence roadmap decisions.
Qualifications:
- Ph.D. with 6+ years, or M.S. with 8+ years, or B.S. with 10+ years in relevant fields.
- Pharmaceutical/biotech/life sciences/healthcare experience; laboratory/manufacturing/process development or research environment experience.
- Knowledge of scientific data platforms, lab informatics systems, and instrument-generated data.
- Experience in data/software/analytics engineering; leading technical teams and enterprise/scientific data programs.
- Enterprise-scale pipelines/data products; cross-functional initiatives.
- Databricks, cloud data platforms, SQL, Python, modern ETL; data modeling, metadata/ontology/master data; familiarity with data lakes/lakehouses/warehouses/knowledge graphs.
- Understanding of AI/ML data requirements.
Required skills: Cross-functional leadership; data engineering/modeling; digital transformation; lab informatics; predictive analytics; regulatory compliance.
Benefits (if applicable): annual bonus and long-term incentive (if applicable) and comprehensive benefits including medical/dental/vision, retirement (401(k)), paid holidays, vacation, compassionate and sick days.
Application: Apply via https://jobs.merck.com/us/en (or Workday Jobs Hub). Application deadline is stated on the posting.