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.
.
