Data Engineering Manager & Architect (Hybrid Leadership/Architect Role)

Job Title: Data Engineering Manager & Architect (Hybrid Leadership/Architect Role)

Experience Required: 15+ Years

Time Zone Coverage: Eastern Time (ET) - required overlap with client leadership and onshore/offshore teams

Domain: Life Sciences (Highly Regulated Environment)

Cloud/Platform: Microsoft Azure, Databricks

About the Role

We are seeking a seasoned Data Engineering Manager/Architect to lead complex data migration and data engineering initiatives within a highly regulated life sciences environment. This is a hybrid leadership and technical architecture role - the ideal candidate is equally comfortable engaging directly with client executives and stakeholders as they are designing and overseeing the technical implementation of enterprise-scale data solutions on Azure and Databricks.

The candidate will serve as the primary technical and program-level point of contact for client leadership, translating business requirements into scalable architectures, driving execution across onshore/offshore teams, and ensuring delivery excellence in a regulated data ecosystem.

Key Responsibilities

• Work closely and daily with client leadership and business stakeholders to gather, clarify, and prioritize data migration requirements across multiple business domains/experiences.
• Architect, design, and implement end-to-end data migration, data quality, and ETL solutions on Azure and Databricks, ensuring alignment with enterprise standards and regulatory requirements.
• Own and track migration initiatives to closure - from requirements gathering through design, build, testing, and go-live.
• Partner with the Release Train Engineer (RTE) and program teams to align data engineering deliverables with broader program/Agile release cadences.
• Manage and coordinate an onshore/offshore delivery model, ensuring consistent execution, quality, and communication across distributed teams.
• Provide strong technical and architectural leadership, including guidance on data modeling, pipeline design, schema versioning/evolution, and platform best practices.
• Drive problem resolution across technical, process, and stakeholder-related issues, escalating and resolving blockers proactively.
• Take full ownership and accountability for program outcomes, timelines, and stakeholder satisfaction.
• Ensure all solutions comply with data governance, quality, and regulatory requirements specific to the life sciences domain.
• Lead stakeholder engagement activities, including status reporting, roadmap alignment, and executive communication.
• Champion best practices in data analysis, data quality frameworks, and ETL design across the engineering team.

Required Skills & Experience

• 15+ years of overall experience in Data Engineering, with proven experience in leadership/architect hybrid roles.
• Deep hands-on and architectural expertise in:
  • Microsoft Azure (cloud data services)
  • Databricks (platform architecture, pipeline design, performance optimization)
  • Data Migration – large-scale, multi-domain migration programs
  • Data Analysis and Data Quality frameworks/tooling
  • ETL design, development, and orchestration
• Demonstrated experience working in a highly regulated environment, ideally life sciences/pharma.
• Strong understanding of schema versioning and schema evolution strategies in enterprise data platforms.
• Experience partnering with an RTE (Release Train Engineer) and working within SAFe/Agile program structures.
• Proven track record managing or working within an onshore/offshore delivery model.
• Strong stakeholder management skills - able to engage confidently with client leadership and cross-functional business teams.
• Excellent problem-solving, ownership, and program-driving capabilities; comfortable being accountable for outcomes, not just deliverables.
• Ability to work core hours aligned to Eastern Time (ET).

Preferred / Nice-to-Have Skills

• Knowledge of Microsoft Dataverse and Microsoft Dynamics 365.
• Prior experience in life sciences-specific data domains (e.g., clinical, regulatory, commercial, or R&D data).
• Familiarity with data governance and compliance frameworks common in regulated industries (e.g., GxP, 21 CFR Part 11, HIPAA where applicable).

What Success Looks Like in This Role

• Client leadership views this person as a trusted technical advisor and program driver, not just an execution resource.
• Data migration programs are delivered on time, with strong quality and minimal escalations.
• Architecture decisions are scalable, well-documented, and enable clean schema evolution over time.
• Onshore/offshore teams operate cohesively under this person's technical and program guidance.
• Issues are resolved proactively, with clear ownership and communication back to stakeholders.