Lead Data Engineering & Governance
New York, NY | Full-Time
Location: New York, NY — On-Site
Experience: Minimum 10 Years
Industry: Pharma / Life Sciences (Preferred)
Function: Data Engineering, Data Governance, AI Consulting
Note: This position is not eligible for Immigration Sponsorship at this time.
ROLE OVERVIEW
Fractal Analytics is looking for a Data Engineer & Governance Lead to join its Pharma AI practice and serve as the primary data consulting authority on a large-scale enterprise account in the pharmaceutical sector. Based in New York and working on-site with the client, this individual will own the data strategy, architecture, and governance agenda across several interconnected workstreams - from pipeline modernization and data catalog design to forecasting infrastructure and gross-to-net analytics.
This is a senior consulting role that requires equal depth in technical execution and stakeholder communication. The ideal candidate is a practitioner who can design a Snowflake data model in the morning, present a governance roadmap to a VP in the afternoon, and articulate how AI changes the data stack in between. You will work alongside Fractal's product and analytics teams while functioning as a visible, trusted presence for the client's data and analytics leadership.
KEY RESPONSIBILITIES
Data Engineering & Architecture
- Lead the design and delivery of scalable data pipelines and data platform solutions built on AWS and Snowflake, ensuring reliability, performance, and cost efficiency at enterprise scale.
- Define data modeling standards, schema governance, and ingestion patterns appropriate to the client's commercial and operational data landscape.
- Drive adoption of modern engineering practices including CI/CD for data, automated testing, lineage tracking, and pipeline observability.
- Advise on lakehouse design, semantic layer implementation, and analytical infrastructure to support both traditional BI and AI-native consumption patterns.
Data Governance
- Establish and operationalize a comprehensive data governance framework covering data classification, metadata management, stewardship ownership, and access control.
- Lead the design and rationalization of the client's data catalog strategy, ensuring that data assets across commercial, financial, and operational domains are discoverable, trusted, and compliant.
- Leverage tools like Cortex AI, dbt, and Power BI (or similar solutions) to define, implement, and continuously monitor data quality frameworks that ensure accuracy, completeness, consistency, and reliability across systems.
- Partner with the client's legal, compliance, and IT security teams to ensure all data practices meet applicable regulatory requirements, including HIPAA and pharma-specific standards.
- Define and monitor data quality SLAs, instill data quality ownership across business teams, and drive measurable improvement in data reliability over time.
AI-Enabled Data Strategy
- Bring an AI-native perspective to every data engagement — identifying opportunities where large language models, retrieval-augmented generation, or agentic pipelines can accelerate insight delivery or reduce manual data processes.
- Evaluate and advise on the AI readiness of the client's data infrastructure, including vector storage, embedding pipelines, and integration with LLM-based applications.
- Collaborate with Fractal's AI product teams to ensure that data platforms are architected for downstream AI and machine learning consumption, not just traditional analytics.
Client Engagement & Consulting Leadership
- Serve as the primary data and governance thought-partner for senior client stakeholders, including data platform owners, analytics leads, and commercial operations leadership.
- Facilitate workshops, design sessions, and executive briefings, translating complex technical architecture into clear, decision-ready narratives.
- Prepare and present structured deliverables - roadmaps, framework assessments, solution architectures - that reflect both technical rigor and business alignment.
- Mentor and guide junior team members on Fractal's delivery standards, consulting craft, and pharma domain context.
- Be in client office 4 days a week (New York)
QUALIFICATIONS
Required
- Minimum 10 years of experience in data engineering, data governance, data architecture, or data consulting, with a strong preference for pharma or life sciences industry exposure.
- Hands-on proficiency with AWS data services, including S3, Glue, Redshift, Lake Formation, and Step Functions.
- Deep working knowledge of Snowflake - data modeling, Snowpipe, dynamic tables, role-based access control, data quality with Cortex AI and performance tuning.
- Demonstrated experience designing and delivering enterprise data governance programs, including data cataloging, data quality, and metadata management.
- Familiarity with pharma commercial data domains - prescription analytics (TRx, NBRx), HCP segmentation, claims