Education: Ph.D. with 6+ years OR Master's with 12+ years in Computer Science, Data Science, Data Engineering, Applied Mathematics, Bioinformatics, or related discipline.
Strong understanding of LIMS/ELN systems like Benchling , LabWare or similar is mandatory.
Experience: 8+ years in data architecture/engineering in a scientific or manufacturing context; proven delivery in hybrid cloud/on‑prem data lakes/warehouses.
Cloud data platforms: Expertise in AWS, Snowflake, Databricks or comparable cloud data platforms and ecosystems.
Database Platforms: Expertise in NoSQL, in-memory, Graph and relational databases, which form the backbone of our operations.
Tooling & Platforms: Expert in data lake architectures (curation/serving layers), metadata/catalog tools, ELT/ETL data transformation frameworks;
Analytics Enablement: Delivered governed, reusable datasets powering visualization tools like Spotfire , Tableau or Power BI ;
Ways of Working: Working knowledge of Scaled Agile (SAFe) - backlog refinement, PI planning and release management.
Experience in preclinical/bioprocess domains (samples, assays, batches, equipment, methods).
Experience with Lab Systems for bioprocessing.
Prior work aligning data standards across R&D, QA, and Manufacturing (data integrity, traceability).
Core Competencies
Build Data Architectures that span lab, data, and analytics ecosystems.
Strong Communications
Ability to Influence :
Build Roadmaps .
Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment withou
Benefits
Health insuranceDental insuranceVision insurance401(k)Equity / stock optionsPerformance bonusParental leave
Additional Information
The Data Enablement and Analytics (DEA) team, within the PAPD (Product, Analytics and Process Development) organization, is a multi-functional team that drives PAPD's digitalization efforts by making data usable and useful!
The Data Management Architect defines and governs the end-to-end architecture of data systems that power preclinical science and operations. You will architect domain-driven data models, curated datasets, and integration patterns across data lakes, lab systems and analytical tools, while enabling self-service visualizations. You will drive data quality, lineage, metadata and data catalog standards, and platform patterns. To accomplish this, you will partner with numerous teams and departments and deliver value through Agile approaches.
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 or 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.
Regeneron · Tarrytown