Data Engineering Product Owner – Pharma Clinical Trials | Longterm Contract

Role Summary
The Data Engineering Product Owner leads the roadmap and delivery of data engineering products that power clinical trial analytics, regulatory reporting, and study operations across the pharma R&D organization. This role sits at the intersection of clinical data science, IT/data engineering, and business stakeholders (Clinical Operations, Biostatistics, Data Management, Regulatory), translating clinical trial data needs into a prioritized backlog delivered on an AWS-based data platform (Redshift, Glue, Lambda, PostgreSQL). The Product Owner is accountable for the value, quality, and compliance (GxP/21 CFR Part 11) of clinical data pipelines and analytics products, acting as the primary liaison between engineering teams and clinical business stakeholders.
Reports to: Director/Head of Data Engineering or Clinical Data Platform Lead. Works closely with: Clinical Data Management, Biostatistics/SAS Programming, Clinical Systems (Veeva Vault) teams, Data Architecture, and Agile delivery teams
Key Responsibilities
Own and prioritize the product backlog for clinical data engineering pipelines, analytics products, and clinical data integrations, balancing regulatory deadlines, study milestones, and business value.
Translate requirements from Clinical Operations, Biostatistics, Data Management, and Regulatory Affairs into clear user stories, acceptance criteria, and technical specifications for the engineering team.
Define and communicate the product vision and roadmap for clinical data platforms, aligning with clinical trial timelines (study start-up, interim analysis, database lock, submission).
Partner with data engineers and architects to design ETL/ELT pipelines that ingest data from clinical systems (EDC, CTMS, eTMF, Veeva Vault) into the AWS data platform (S3, Glue, Redshift, PostgreSQL).
Facilitate agile ceremonies (sprint planning, backlog grooming, sprint review, retrospectives) and act as the voice of the customer throughout the delivery lifecycle.
Define data quality, validation, and reconciliation requirements to ensure clinical data integrity across source systems and downstream analytics/reporting layers.
Ensure deliverables meet GxP, 21 CFR Part 11, HIPAA/GDPR, and data privacy requirements applicable to clinical trial data.
Collaborate with Analytics/BI teams to define self-service reporting and dashboarding requirements (e.g., enrollment tracking, site performance, safety signal monitoring, data quality dashboards).
Manage stakeholder expectations, communicate delivery status, risks, and trade-offs to clinical and IT leadership.
Support UAT (user acceptance testing), validation documentation, and change control processes required in a regulated clinical environment.
Monitor product performance post-release and drive continuous improvement of data pipelines, cost efficiency (AWS resource optimization), and platform reliability.
Required Qualifications & Experience
Bachelor's degree in Computer Science, Information Systems, Life Sciences, or a related field (Master's preferred).
15+ years of experience in data engineering, data product management, or IT roles within pharma, biotech, or life sciences, including 6+ years specifically as a Product Owner on data/analytics products.
Demonstrated experience owning a backlog for data engineering or analytics products built on AWS (Redshift, Glue, Lambda, S3) and/or PostgreSQL.
Direct experience with clinical trial data and systems (Veeva Vault, EDC, CTMS, eTMF, or similar) in a regulated (GxP) environment.
Solid understanding of ETL/ELT concepts, data modeling, and analytics/BI delivery.
Proven experience working in Agile/Scrum delivery teams, with certification (CSPO, PSPO, or SAFe Product Owner/Product Manager) preferred.
Strong written and verbal communication skills, with the ability to translate between technical and clinical/business audiences.
Experience writing user stories, acceptance criteria, and managing a product backlog in tools such as Jira or Azure DevOps.
Preferred Qualifications
AWS certification (AWS Certified Cloud Practitioner, Data Analytics Specialty, or Solutions Architect Associate).
Hands-on familiarity with SQL for data validation and exploratory analysis.
Experience with CDISC standards (SDTM/ADaM) and clinical data warehousing.
Exposure to data visualization/BI tools (Tableau, Power BI, QuickSight, Spotfire) used for clinical trial reporting.
Experience supporting FDA/EMA submissions or inspection readiness from a data systems perspective.
Familiarity with data governance, master data management, and metadata management practices in a life sciences context.
Experience in a global, cross-time-zone delivery environment with offshore/nearshore engineering teams.
Key Competencies & Soft Skills
Stakeholder management: builds trust with clinical, regulatory, and technical stakeholders who have differing priorities and vocabularies.
Prioritization and trade-off judgment: balances regulatory deadlines, technical debt, and business value under time pressure.
Clear communication: explains technical concepts to clinical audiences and clinical/regulatory requirements to engineers.
Compliance mindset: treats data quality, traceability, and audit readiness as first-class requirements, not afterthoughts.
Ownership and accountability: drives decisions on scope and priority rather than deferring them upward.
Collaborative leadership: works well in cross-functional, matrixed teams without direct authority over all contributors.
Adaptability: comfortable with ambiguity as study requirements and regulatory guidance evolve.

Work arrangement
Yes