Sr Staff Engineer, Data Management (DEA)
Regeneron
4 days ago
Remote friendly (Tarrytown, NY)
United States
IT
A Typical Day In The Role Might Involve
- 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 toward a central data platform (e.g., research data lake/connected data marts); design streaming and batch data flow patterns (ETL vs ELT).
- 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.
- LIMS/ELN Architecture and Solution Delivery: Model experiment workflows; capture structured context at source; ensure compliant, scalable lab platforms (e.g., Benchling, LabWare LIMS).
- SAFe Ways of Working: Act as product manager and program lead to define roadmap and continuous delivery mechanism using Scaled Agile Frameworks.
- Collaboration & Change Enablement: Co-create roadmaps; conduct design reviews; mentor engineers and citizen developers.
Minimum Qualifications
- Ph.D. with 6+ years OR Master’s with 12+ years in CS/Data Science/Data Engineering/Applied Math/Bioinformatics or related.
- Mandatory strong understanding of LIMS/ELN systems (e.g., Benchling, LabWare).
- 8+ years in data architecture/engineering in scientific/manufacturing context; delivery in hybrid cloud/on-prem data lakes/warehouses.
- Expertise in AWS, Snowflake, Databricks (or comparable) cloud data platforms.
- Expertise in NoSQL, in-memory, Graph, and relational databases.
- Expert in data lake architectures (curation/serving), metadata/catalog tools, and ELT/ETL frameworks.
- Delivered governed, reusable datasets powering Spotfire/Tableau/Power BI.
- Working knowledge of Scaled Agile (SAFe): backlog refinement, PI planning, release management.
Preferred Qualifications
- Experience in preclinical/bioprocess domains; lab systems for bioprocessing.
- Prior work aligning data standards across R&D, QA, and Manufacturing (data integrity, traceability).
Application Instructions
- Apply now.
- 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 toward a central data platform (e.g., research data lake/connected data marts); design streaming and batch data flow patterns (ETL vs ELT).
- 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.
- LIMS/ELN Architecture and Solution Delivery: Model experiment workflows; capture structured context at source; ensure compliant, scalable lab platforms (e.g., Benchling, LabWare LIMS).
- SAFe Ways of Working: Act as product manager and program lead to define roadmap and continuous delivery mechanism using Scaled Agile Frameworks.
- Collaboration & Change Enablement: Co-create roadmaps; conduct design reviews; mentor engineers and citizen developers.
Minimum Qualifications
- Ph.D. with 6+ years OR Master’s with 12+ years in CS/Data Science/Data Engineering/Applied Math/Bioinformatics or related.
- Mandatory strong understanding of LIMS/ELN systems (e.g., Benchling, LabWare).
- 8+ years in data architecture/engineering in scientific/manufacturing context; delivery in hybrid cloud/on-prem data lakes/warehouses.
- Expertise in AWS, Snowflake, Databricks (or comparable) cloud data platforms.
- Expertise in NoSQL, in-memory, Graph, and relational databases.
- Expert in data lake architectures (curation/serving), metadata/catalog tools, and ELT/ETL frameworks.
- Delivered governed, reusable datasets powering Spotfire/Tableau/Power BI.
- Working knowledge of Scaled Agile (SAFe): backlog refinement, PI planning, release management.
Preferred Qualifications
- Experience in preclinical/bioprocess domains; lab systems for bioprocessing.
- Prior work aligning data standards across R&D, QA, and Manufacturing (data integrity, traceability).
Application Instructions
- Apply now.