Associate Director, Data Engineer: DSCS Digital Data Strategy
Merck
June 25, 2026
Remote friendly (Rahway, NJ)
United States
IT
Associate Director, Data Engineer (Biologics)
Responsibilities:
- Serve as domain owner for biologics data engineering; maintain awareness of projects, sources, systems, and data flows.
- Inform DSCS Digital Data Strategy.
- Design and implement robust, scalable ETL/ELT pipelines ingesting biologics data (process historians, chromatography, electronic lab notebooks, analytical instruments).
- Deliver analysis-ready datasets (process characterization models, data lineage tracking, multivariate analytics, cross-site manufacturing connectivity).
- Define/enforce data standards, metadata schemas, and ontology mappings for interoperability.
- Anticipate automation-driven new data streams; align with automation colleagues on required pipeline/ontology updates.
- Own/govern system-of-record standards for biologics to ensure consistent configuration and data entry.
- Catalog processes, analytical methods, instruments, and digital systems; create data landscape map.
- Develop dashboards/reports enabling exploration across runs, molecules, scales, and sites.
- Influence data strategy by improving source data capture and reducing friction between experimentation and modeling.
- Mentor data engineers across modalities; govern ontology alignment.
- Maintain/version pipeline code in GitHub (reviews, documentation, deployment).
- Partner with process development, analytical, and manufacturing teams; demonstrate strong communication/collaboration.
Education Minimum:
- Ph.D. (or M.S./B.S.) in relevant fields with 3/5/7+ years industrial/pharmaceutical or relevant experience.
Required Skills/Experience:
- Proficient in Python and/or R; comfortable with Jupyter/Posit-RStudio/VS Code.
- Solid SQL; ETL/ELT data pipelines in scientific/pharmaceutical context.
- Familiar with AWS/Azure/GCP.
- Working knowledge of process models, multivariate/statistical tools consuming experimental data.
- Experience defining/enforcing data standards/metadata/ontology mappings.
- Git/GitHub; lead technical initiatives and mentor.
Preferred:
- Hands-on biologics process development (chromatography/filtration/purification/formulation) plus transition to data engineering/science.
- Databricks (Delta Lake, orchestration), dashboards (Streamlit/Shiny/PowerBI/Spotfire/Tableau).
- Ontology frameworks (e.g., Allotrope, ISA-88, OPC-UA), DoE/process characterization (CPPs/CQAs), data lineage, regulatory knowledge (ICH Q8–Q12), lab automation and cross-site integration.
Benefits:
- Eligible for annual bonus and long-term incentive (if applicable); comprehensive benefits (medical/dental/vision, retirement/401(k), paid holidays, vacation, sick/compassionate days).
Application Instructions:
- Apply via https://jobs.merck.com/us/en (deadline stated on posting).
Responsibilities:
- Serve as domain owner for biologics data engineering; maintain awareness of projects, sources, systems, and data flows.
- Inform DSCS Digital Data Strategy.
- Design and implement robust, scalable ETL/ELT pipelines ingesting biologics data (process historians, chromatography, electronic lab notebooks, analytical instruments).
- Deliver analysis-ready datasets (process characterization models, data lineage tracking, multivariate analytics, cross-site manufacturing connectivity).
- Define/enforce data standards, metadata schemas, and ontology mappings for interoperability.
- Anticipate automation-driven new data streams; align with automation colleagues on required pipeline/ontology updates.
- Own/govern system-of-record standards for biologics to ensure consistent configuration and data entry.
- Catalog processes, analytical methods, instruments, and digital systems; create data landscape map.
- Develop dashboards/reports enabling exploration across runs, molecules, scales, and sites.
- Influence data strategy by improving source data capture and reducing friction between experimentation and modeling.
- Mentor data engineers across modalities; govern ontology alignment.
- Maintain/version pipeline code in GitHub (reviews, documentation, deployment).
- Partner with process development, analytical, and manufacturing teams; demonstrate strong communication/collaboration.
Education Minimum:
- Ph.D. (or M.S./B.S.) in relevant fields with 3/5/7+ years industrial/pharmaceutical or relevant experience.
Required Skills/Experience:
- Proficient in Python and/or R; comfortable with Jupyter/Posit-RStudio/VS Code.
- Solid SQL; ETL/ELT data pipelines in scientific/pharmaceutical context.
- Familiar with AWS/Azure/GCP.
- Working knowledge of process models, multivariate/statistical tools consuming experimental data.
- Experience defining/enforcing data standards/metadata/ontology mappings.
- Git/GitHub; lead technical initiatives and mentor.
Preferred:
- Hands-on biologics process development (chromatography/filtration/purification/formulation) plus transition to data engineering/science.
- Databricks (Delta Lake, orchestration), dashboards (Streamlit/Shiny/PowerBI/Spotfire/Tableau).
- Ontology frameworks (e.g., Allotrope, ISA-88, OPC-UA), DoE/process characterization (CPPs/CQAs), data lineage, regulatory knowledge (ICH Q8–Q12), lab automation and cross-site integration.
Benefits:
- Eligible for annual bonus and long-term incentive (if applicable); comprehensive benefits (medical/dental/vision, retirement/401(k), paid holidays, vacation, sick/compassionate days).
Application Instructions:
- Apply via https://jobs.merck.com/us/en (deadline stated on posting).