Role Description:

We are seeking a Senior Data Engineering Manager with a strong background in Regulatory or Integrated Product Teams within the Biotech or Pharmaceutical domain. This role will lead the end-to-end data strategy and execution for regulatory product submissions, lifecycle management, and compliance reporting, ensuring timely and accurate delivery of regulatory data assets across global markets.You will be embedded in a cross-functional Regulatory Integrated Product Team (IPT) and serve as the data and technology lead, driving integration between scientific, regulatory, and engineering functions to support submission-ready data and regulatory intelligence solutions.

Roles & Responsibilities:

Functional Skills:

Lead the engineering strategy and implementation for end-to-end regulatory operations, including data ingestion, transformation, integration, and delivery across regulatory systems.
Serve as the data engineering SME in the Integrated Product Team (IPT) to support regulatory submissions, agency interactions, and lifecycle updates.
Collaborate with global regulatory affairs, clinical, CMC, quality, safety, and IT teams to gather submission data requirements and translate them into data engineering solutions.
Manage and oversee the development of data pipelines, data models, and metadata frameworks that support submission data standards (e.g., eCTD, IDMP, SPL, xEVMPD).
Enable integration and reporting across regulatory information management systems (RIMS), EDMS, clinical trial systems, and lab data platforms.
Implement data governance, lineage, validation, and audit trails for regulatory data workflows, ensuring GxP and regulatory compliance.
Guide the development of automation solutions, dashboards, and analytics that improve visibility into submission timelines, data quality, and regulatory KPIs.
Ensure interoperability between regulatory data platforms and enterprise data lakes or lakehouses for cross-functional reporting and insights.
Collaborate with IT, data governance, and enterprise architecture teams to ensure alignment with overall data strategy and compliance frameworks.
Drive innovation by evaluating emerging technologies in data engineering, graph data, knowledge management, and AI for regulatory intelligence.
Lead, mentor, and coach a small team of data engineers and analysts, fostering a culture of excellence, innovation, and delivery.
Drive Agile and Scaled Agile (SAFe) methodologies, managing sprint backlogs, prioritization, and iterative improvements to enhance team velocity and project delivery.
Stay up-to-date with emerging data technologies, industry trends, and best practices, ensuring the organization leverages the latest innovations in data engineering and architecture.

Must-Have Skills:

8-12 years of experience in data engineering or data architecture, with 3+ years in a senior or managerial capacity, preferably within the biotech or pharmaceutical industry.
Proven experience supporting regulatory functions, including submissions, tracking, and reporting for FDA, EMA, and other global authorities.
Experience with ETL/ELT tools, data pipelines, and cloud-based data platforms (e.g., Databricks, AWS, Azure, or GCP).
Familiarity with regulatory standards and data models such as eCTD, IDMP, HL7, CDISC, and xEVMPD.
Deep understanding of GxP data compliance, audit requirements, and regulatory submission processes.
Experience with tools like Power BI, Tableau, or Qlik for regulatory dashboarding and visualization is a plus.
Strong project management, stakeholder communication, and leadership skills, especially in matrixed, cross-functional environments.
Ability to translate technical capabilities into regulatory and business outcomes.Prepare team members for stakeholder discussions by helping assess data costs, access requirements, dependencies, and availability for business scenarios.

Good-to-Have Skills:

Prior experience working on integrated product teams or regulatory transformation programs.
Knowledge of Regulatory Information Management Systems (RIMS), Veeva Vault RIM, or Master Data Management (MDM) in regulated environments.
Familiarity with Agile/SAFe methodologies and DevOps/DataOps best practices.

Education and Professional Certifications

12 to 15 years of experience in Computer Science, IT or related field
Scaled Agile SAFe certification preferred
Project Management certifications preferred

Soft Skills:

Excellent analytical and troubleshooting skills
Strong verbal and written communication skills
Ability to work effectively with global, virtual teams
High degree of initiative and self-motivation
Ability to manage multiple priorities successfully
Team-oriented, with a focus on achieving team goals
Strong presentation and public speaking skills

Sr Data Engineering Manager