Senior Data Engineer (AI)

Location: Hybrid, requiring 3 days per week in office, primarily in the New York City and Boston metro areas. Applicants from the Research Triangle, North Carolina, and the San Francisco Bay Area may also be considered. Applicants must reside in these locations or be willing to relocate.

Total compensation range: $185,500–$232,000 per year, plus equity, comprehensive benefits, and perks.

Company

hirify.global is a technology and AI-driven pharmaceutical company building platforms and capabilities to accelerate drug development and clinical trials.

What you will do

• Design and operate production data systems ingesting clinical, operational, and third-party vendor data.
• Own canonical data models, data contracts, transformations, orchestration, warehouse models, and downstream interfaces.
• Partner with Product Engineering on application data models, APIs, events, source-system contracts, and data access patterns.
• Partner with Data Science on training datasets, feature pipelines, data interfaces, and machine learning use cases.
• Build data products for clinical operations, asset evaluation, business development, analytics, machine learning, and AI-enabled employees and agents.
• Establish data quality, testing, freshness, lineage, documentation, observability, governance, access controls, and incident-response practices.

Requirements

• 5+ years of relevant data engineering experience building and operating production data systems.
• Experience with pharmaceutical, biology, HIPAA, or other regulated biotech data is required.
• Strong Python and SQL skills with deep experience in data modeling and warehouse systems, especially Snowflake.
• Experience with Dagster or equivalent orchestration and transformation tooling such as dbt.
• Experience with data contracts, schema evolution, data quality testing, observability, lineage, production incident response, and complex source-data integration.
• Working knowledge of Docker, GitHub, Terraform or OpenTofu, AI tools, and validated computerized systems.

Nice to have

• Experience working within and building validated computerized systems (CSV).

Culture & Benefits

• Hybrid work model with three office days per week.
• Collaboration across Product Engineering, Data Science, Clinical Operations, Data Management, Business Development, and other non-technical functions.
• Opportunities to mentor engineers and improve engineering practices across the organization.
• Equity, comprehensive benefits, and generous perks.