Senior Staff Engineer, Data Management

Role Summary

The Senior Staff Engineer, Data Management will lead the architecture and governance of data systems powering preclinical science and operations. You will architect domain-driven data models, curated datasets, and integration patterns across data lakes, lab systems, and analytical tools, enabling self-service visualizations. You will drive data quality, lineage, metadata and catalog standards, and platform patterns, partnering with multiple teams and delivering value through Agile practices.

Responsibilities

• Enterprise Data Architecture (Preclinical): Define data models for preclinical entities (samples, assays, lots, batches, instruments, methods), harmonized across the data ecosystem; establish golden-record, lineage, and System of record.
• Data Platform Design: Partner with IT teams to continue our journey to a central data platform like the Research data lake or connected data marts. Partner with data engineering teams to design streaming and batch data flow (ETL vs ELT) patterns and deliver such solutions.
• Visualization & Semantics: Publish governed, analysis-ready semantic layers and reusable data marts; define KPI/metric definitions; enable self-service in Spotfire/Tableau with certified data sources and good performance.
• Data Management & Governance: Stand up data catalog/metadata standards, reference/master data strategies, quality controls, and lifecycle policies; partner with business data stewards in PAPD.
• LIMS/ELN Architecture and Solution Delivery: Partner with platform owners and lab teams to model experiment workflows, capture structured context at source, and ensure compliant, scalable Lab platforms like Benchling or LabWare LIMS.
• SAFe Ways of Working: Act as the overall product manager and program Lead – define our roadmap and continuous delivery mechanism using Scaled Agile Frameworks.
• Collaboration & Change Enablement: Co-create roadmaps with PAPD functional leads and department data experts; conduct design reviews; mentor engineers and citizen developers.

Qualifications

• Required: Strong understanding of LIMS/ELN systems like Benchling, LabWare or similar.
• Required: Experience — 8+ years in data architecture/engineering in a scientific or manufacturing context; proven delivery in hybrid cloud/on-prem data lakes/warehouses.
• Required: Cloud data platforms — Expertise in AWS, Snowflake, Databricks or comparable cloud data platforms and ecosystems.
• Required: Database Platforms — Expertise in NoSQL, in-memory, Graph and relational databases, which form the backbone of our operations.
• Required: Tooling & Platforms — Expert in data lake architectures (curation/serving layers), metadata/catalog tools, ELT/ETL data transformation frameworks.
• Required: Analytics Enablement — Delivered governed, reusable datasets powering visualization tools like Spotfire, Tableau or Power BI.
• Required: Ways of Working — Working knowledge of Scaled Agile (SAFe) - backlog refinement, PI planning and release management.

Education

• Bachelor’s degree in computer science, Information Systems, Bioinformatics, Biomedical Engineering, or related field.

Skills

• Build Data Architectures that span lab, data, and analytics ecosystems.
• Strong Communications
• Ability to Influence
• Build Roadmaps
• Continuous delivery using Agile