Career Category

Engineering

Job Description

Position Overview

The GCF5 Senior Data Engineer is the senior technical leader for the Enterprise Data Foundation (EDF) / Common Data Model pillar. They define and socialize canonical data standards, contracts, and patterns; lead multi-team delivery; mentor GCF4 engineers; and translate scientific needs into scalable data platform designs. They own pillar-level adoption, reliability, and Service Level Agreement (SLA) / Service Level Objective (SLO) outcomes, and influence cross-team engineering quality.

This role reports to the GCF7 leader and partners closely with peer GCF5 domain leads across SCIP to ensure cohesive, scalable platform evolution.

Core Responsibilities

• Own the technical roadmap and delivery of the Enterprise Data Foundation capability within SCIP.
• Define and govern canonical data models, schema standards, and contract-first integration patterns.
• Establish and enforce data contracts to ensure reliable, versioned integrations.
• Design and implement scalable ingestion, transformation, and validation pipelines aligned to platform standards.
• Define and operationalize data lineage and metadata practices.
• Establish automated data quality and conformance validation frameworks.
• Lead architecture reviews for data domain changes and migrations.
• Mentor engineers and elevate data engineering standards.
• Partner with scientific and analytics stakeholders to translate research workflows into durable data products.

Core Competencies

• Deep expertise in the assigned pillar (Enterprise Data Foundation (EDF) / Common Data Model (CDM) ) with evidence of standard‑setting and reuse.
• Systems design at scale (enterprise data platforms); performance, security, and observability fundamentals.
• Product/engineering thinking: road mapping, prioritization, and outcome‑oriented delivery.
• Stakeholder influence across science, engineering, and governance forums; crisp written/verbal communication.

Core Success Measures

• Adoption of canonical data models across applicable systems.
• Data contract compliance rate and reduction in schema-breaking changes.
• Lineage completeness and auditability of governed datasets.
• Reduction in downstream data defects.
• Time-to-onboard new data domains into standardized patterns.
• Measurable improvements in data reliability and reuse.

Key Relationships

• Collaborates with GCF6 Group Lead and cross‑functional leaders (R&D/PD/Dev).
• Mentors and develops GCF4 Data and Software Engineers, partners with platform, data, ML, and research teams.
• Interfaces with governance (architecture, security, compliance) and vendor/partner teams.

Decision Authority

• Approve designs within the pillar; define and waive standards/patterns with rationale.
• Recommend buy‑vs‑build; commit pillar resources to meet SLAs/SLOs; escalate risks.
• Prioritize pillar backlog and roadmap in alignment with strategy and OKRs.

Qualifications

Basic Qualifications:

• BS+8 / MS+6 / PhD in CS/Engineering/Data disciplines.
• Demonstrated production delivery experience in enterprise data platforms at scale.
• Demonstrated literacy in a relevant scientific domain (e.g., biology, chemistry, therapeutic discovery).
• Preferred Qualifications:
• Depth in the assigned pillar (Enterprise Data Foundation (EDF) / Common Data Model) (EDF/CDM).
• Kubernetes and continuous integration/continuous delivery (CI/CD) at scale; observability, performance tuning, and security-by-design.
• Evidence of standard‑setting and cross‑team influence; mentoring experience.

.