> Markdown version of [/jobs/ext/3050867-associate-director-data-engineer-dscs-digital-technologies](https://www.wearedevelopers.com/jobs/ext/3050867-associate-director-data-engineer-dscs-digital-technologies). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Associate Director, Data Engineer, DSCS Digital Technologies

- **Company:** Merck Sharp & Dohme LLC
- **Location:** West Point, PA, United States
- **Experience:** Experienced
- **Salary:** $129,000.0 - $203,100.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Amazon S3, Data Analysis, Catalyst (Software), Cloud Storage, Information Engineering, Data Governance, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Visualization, Relational Databases, Digital Data, Experimental Data, Graph Database, Supervisory Control and Data Acquisition (SCADA), Python (Programming Language), Laboratory Information Management Systems, Machine Learning, RStudio, Power BI, SQL Databases, Tableau (Software), Jupyter Notebook, Data Processing, Model-Driven Development, Data Ingestion, Jupyter, Build Management, Information Technology, Data Analytics, Data Management, Spotfire, Dataiku, Streamlit Framework, Data Pipelines, Databricks, Data Generation
- **Published:** September 24, 2026
- **Apply:** https://www.businessworkforce.com/job.asp?id=3402978744&tx=TT4138TYV&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Ph.D. in Computer Science, Data Science, Engineering, Chemistry, Physics, Biology, Pharmaceutical Sciences, or a closely related field, with at least 3 years of industrial/pharmaceutical or relevant experience; OR
 * M.S. in Computer Science, Data Science, Engineering, Chemistry, Physics, Biology, Pharmaceutical Sciences, or a closely related field, with at least 5 years of industrial/pharmaceutical or relevant experience; OR
 * B.S. in Computer Science, Data Science, Engineering, Chemistry, Physics, Biology, Pharmaceutical Sciences, or a closely related field, with at least 7 years of industrial/pharmaceutical or relevant experience.

Required Experience and Skills

 * Hands-on experience in sterile drug product development, sterile DS and DP manufacturing processes, or closely related pharmaceutical development, with a demonstrated transition into a data engineering, data science, or computational role.
 * Experience developing and deploying data pipelines, ETL/ELT workflows, and data integration solutions in a scientific or pharmaceutical context.
 * Proficiency programming in Python and/or R, and with Posit/RStudio/Jupyter.
 * Working knowledge of how data-driven models consume and depend on experimental data, sufficient to anticipate modeler needs and deliver appropriately structured datasets.
 * Excellent communication, creativity, and interpersonal skills.
 * Proven ability to deliver complex solutions under compressed timelines in a dynamic environment.
 * Ability to work in a team environment with cross-functional interactions.
 * Motivation to learn new skills, willingness to take on new challenges, and scientific curiosity.

Preferred Experience and Skills

 * Experience with one or more drug modalities developed internally, such as small molecules, biologics, vaccines, peptides, or drug conjugates.
 * Experience with sterile CMC development workflows, particularly unit operations such as mixing, pooling, pumping, filling, filtration, and freeze-drying.
 * Familiarity with data-driven modeling approaches (e.g., machine learning and statistical models), not necessarily as a modeler, but understanding input/output data requirements and validation data needs.
 * Experience with common process and analytical capabilities used in pharmaceutical development.
 * Familiarity with laboratory data systems (ELN, LIMS, historian/SCADA systems, PAT) and how to extract structured data from them.
 * Experience with data visualization tools (Shiny, Streamlit, Spotfire, Dash, Power BI, or Tableau).
 * Experience connecting to AWS (S3, Redshift, Glue, Athena, SageMaker) as a data source for data visualization.
 * Experience with data pipeline tools such as Dataiku or Databricks.
 * Experience with relational databases, graph databases, and SQL.
 * Knowledge of regulatory expectations relevant to sterile products and model-informed development (e.g., ICH Q8 through Q12, process validation, data integrity).
 * Evidence of cross-functional collaboration spanning laboratory, manufacturing, modeling, and digital teams.
 * Prior contributions to technology transfer, process robustness assessments, or troubleshooting in a sterile manufacturing context., Change Catalyst, Change Catalyst, Customer-Focused, Data Analysis, Databricks Unified Data Analytics Platform, Data Engineering, Data Generation, Data Ingestion, Data Management, Data Modeling Techniques, Data Pipelines, Data Science, Data Transformation, Data Visualization, Design Changes, Detail-Oriented, Engineering Principle, Engineering Standards, Estimation and Planning, Graph Databases, Identifying Customer Needs, Jupyter Notebook, Manufacturing Scale-Up, Model Driven Design, Production Optimization {+ 7 more}, Valid Driving License

## Description

We are seeking an Associate Director to join our Digital Insights team within the Development Sciences and Clinical Supply (DSCS) Digital Technologies organization. Digital is the multiplier that will allow DSCS to deliver better experiments faster, more efficient filing and launch, more robust supply chains, and higher-confidence decisions across the portfolio.

The DSCS Digital Technologies organization is responsible for the invention and application of new digital tools and workflows to support scientists across drug substance development, drug product development, and analytical development. We aspire to embed digital technologies into the fabric of DSCS culture to drive transformational impact. In this Associate Director role, the successful candidate will design, build, and maintain the data foundation that powers data-driven modeling of sterile drug product development. Specifically, the candidate will capture, curate, and deliver experimental and process data from Sterile Product Development (SPD) teams into machine learning, statistical, and hybrid modeling workflows. This role is a critical enabler of our process modeling strategy: using data-driven models, supported by mechanistic understanding where appropriate, to de-risk and optimize sterile drug substance (DS) and drug product (DP) manufacturing processes across biologics and
vaccines.

The ideal candidate has hands-on experience in sterile drug product development and has since transitioned into a data engineering or data science role. This domain depth enables the candidate to work comfortably alongside SPD experimentalists, understand the scientific context of the data being captured, and anticipate the needs of downstream modelers. Familiarity with data-driven modeling approaches, and how they consume experimental data, is strongly preferred, so that the candidate can deliver data in the right format, granularity, and context.

Responsibilities

 * Build strong partnerships with SPD experimentalists, process engineers, and analytical scientists to gather requirements for data solutions that directly feed modeling pipelines.
 * Design and implement robust, scalable data pipelines that ingest experimental and process data from SPD teams (e.g., unit operations such as mixing, pooling, pumping, filling, filtration, and freeze-drying, along with analytical characterization data).
 * Partner directly on process modeling to translate data-driven model requirements into analysis-ready, feature-rich datasets tailored to modeling needs.
 * Define and enforce data standards, metadata schemas, and ontologies that make SPD data interoperable and readily consumable by data-driven modeling workflows.
 * Automate data ingestion from laboratory instruments, electronic lab notebooks, PAT systems, and manufacturing systems, and integrate with cloud-based storage and compute environments.
 * Develop data analysis and visualization workflows that surface insight from SPD data.
 * Design and build dashboards, reports, and data exports for scientific and cross-functional stakeholders.
 * Curate data and define requirements for automating data ingestion at scale.
 * Influence the digital data strategy for SPD, identifying opportunities to improve data capture at the source and reduce friction between experimentation and modeling.
 * Communicate and collaborate effectively across scientific, engineering, and digital disciplines.
 * Embrace and model our core values of inclusion, fostering a supportive culture where all can thrive.
 * Collaborate productively in a dynamic, integrated, and multidisciplinary team environment.
 * Deliver impactful scientific innovation in a team-oriented manner that builds trusted partnerships across broad stakeholder networks.


## Related Videos

- [Industrializing your Data Science capabilities](https://www.wearedevelopers.com/videos/178-industrializing-your-data-science-capabilities)
- [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture)
- [Kubernetes dev is fun, but setup and ops isn't! See a fun PaaS alternative to push any code, ipynbs or even just data!](https://www.wearedevelopers.com/videos/732-kubernetes-dev-is-fun-but-setup-and-ops-isn-t-see-a-fun-paas-alternative-to-push-any-code-ipynbs-or-even-just-data)
- [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data)
- [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery)
- [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning)

## Related Articles

- [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again)
- [Now is the time for industrialized software development](https://www.wearedevelopers.com/magazine/601-now-is-the-time-for-industrialized-software-development)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers)
- [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market)
- [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies)