Associate Director, Pharmaceutical Data Engineer

Job Description

Position Overview:

Digital is the multiplier that will allow Development Sciences and Clinical Supply to deliver better experiments faster, efficient filing and launch, more robust supply chains and higher-confidence decisions across the portfolio. The Development Sciences and Clinical Supply Digital Technologies organization is tasked with the mission to pioneer and deploy innovative digital technologies that drive the acquisition, automation and utilization of data to enhance insights, efficiency, and quality of Development Sciences and Clinical Supply processes and methods.

The Development Sciences and Clinical Supply Digital Technologies organization within our Company Research Laboratories is accountable for driving the digital transformation, data architecture, and technology solutions that enable the execution and operations of the Development Sciences and Clinical Supply ecosystem.

The Associate Director, Digital Operations, is a highly technical role responsible for shifting the organization from traditional BI reporting to a robust, modern data foundation. This role will heavily focus on data engineering, building custom web applications, and deploying advanced AI/Agentic models to solve complex business problems. The data underpinning this work spans the end-to-end clinical and commercial supply chain - from drug substance manufacturing and process orders through drug product packaging, quality notifications, and global distribution.

The Associate Director, Digital Operations, will:

• •Execute solutions to business needs by designing, building, and implementing modern data foundations and pipelines.
• •Employ innovation and technology solutions (e.g., Databricks, Python, Agentic AI) to manage data and generate advanced insights more effectively.
• •Develop custom web applications (WebApps) for Proof-of-Concept solutions that will later be industrialized in our React Platform.
• •Work strategically and tactically to streamline processes and eliminate manual work through advanced automation and machine learning.
• •Contribute to the advancement of the Data Strategy and Strategic Roadmap, supporting the organization's transition toward future-ready systems and intelligent data architectures.

Primary Activities:

• •Data Engineering & Foundations: Design, build, and optimize scalable data pipelines and architectures leveraging Databricks, Python, Dataverse, and advanced SQL - transforming raw SAP, MES, LIMS, and other Operational data from drug substance and drug product manufacturing and supply operations into highly accessible, analytics-ready data foundations.
• •Requirements Translation: Act as a critical bridge between business and technology by deeply understanding stakeholder needs - working with supply chain planners, quality teams, and manufacturing stakeholders across drug substance and drug product functions - and accurately translating those needs into clear business requirements and precise technical specifications for development.
• •Agentic Modeling & AI: Design, test, and implement agentic AI workflows and machine learning models to automate decision-making processes and generate proactive business insights.
• •Web Application Development: Develop and deploy custom, user-friendly WebApps to support business operations, data entry, and interaction with underlying data models.
• •Development & Code Management: Utilize modern development environments (VS Code) and AI coding assistants (Cline) alongside GitHub for robust version control of scripts, applications, and data models to ensure code quality.
• •Systems Architecture: Work closely with data architects to ensure scalable, secure, and efficient data models that support both analytical and transactional workloads.
• •Documentation & Enablement: Document processes, code, data models, and system architectures; provide training and technical support to end-users as new technologies are rolled out.

Required Skills, Education, and Qualifications:

• •Core Technical Stack: Strong expertise in Python and advanced SQL.
• •Data Platforms & Custom Products: Deep, hands-on experience with the Databricks Lakehouse architecture, Delta Lake, and Unity Catalog for robust data governance. Proven experience building custom data products and rapid-prototype front ends (Streamlit/React). Strong familiarity with SAP (or similar ERP/manufacturing systems) as a primary source for complex supply chain and manufacturing data.
• •Business Analysis: Proven track record of gathering complex requirements from non-technical stakeholders and translating them into actionable, technical roadmaps.
• •Agentic AI & Automation: Familiarity with or strong interest in Agentic Modeling, Large Language Models (LLMs), and integrating AI agents into workflows (e.g., using Copilot Studio).
• •Agile & Team Collaboration: Proven experience working in an Agile/Scrum environment, utilizing Jira Cloud for sprint planning, story estimation, and tracking, and Confluence for maintaining robust, multi-system technical documentation.
• •Modern DevTools : High comfort level working in VS Code and actively leveraging AI-assisted coding tools to accelerate development.
• •CI/CD & Version Control : Strong experience using GitHub for version control, collaborative code reviews (PRs), and automated CI/CD pipelines.
• •Analytical Skills: Strong analytical and problem-solving skills to tackle complex data challenges and translate them into technical solutions.
• •Collaboration & Influence: Demonstrated ability to develop strong, trust-based relationships to drive change and execute priorities with a group of technical and non-technical stakeholders.
• •Communication: Excellent written and verbal communication skills; demonstrated ability to communicate technical concepts clearly to different global professional levels.
• •Independence: Independent decision-making abilities with a proactive approach to leading projects and delivering results.
• •Domain Knowledge (preferred): Familiarity with pharmaceutical drug substance or drug product supply chain operations, including concepts such as process orders, batch genealogy, MRP/MPS planning, tech transfer, quality management, or global distribution. Experience working with SAP (MM/PP/QM/SD modules) or related manufacturing execution systems (MES/LIMS) is a strong plus.

Education Experience:

• •M.S. in Computer Science, Data Science, Engineering, Supply Chain Management, Operations Research, or a closely-related quantitative field with at least 5 years of industrial, pharmaceutical, or relevant data engineering experience.
• •B.S. in Computer Science, Data Science, Engineering, Supply Chain Management, Operations Research, Management Information Systems (MIS), or a closely-related quantitative field with at least 7 years of industrial, pharmaceutical, or relevant data engineering experience

Required Skills:

Agent Based Modeling, Automation, CAPA Management, Clinical Supply Chain Management, Customer Experience Optimization, Databricks Unified Data Analytics Platform, Data Engineering, Data Modeling, Data Pipelines, Data Science, Driving Continuous Improvement, Manufacturing Execution Systems (MES), Proof of Concept (POC), Quantitative Analytics

Preferred Skills:

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US and Puerto Rico Residents Only:

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As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics. As a federal contractor, we comply with all affirmative