Senior Bioinformatics Data Engineer (Consultant)

ProPharma is a consulting firm that has been enhancing patient health and wellness for 25 years by partnering with biotech, med device, and pharmaceutical organizations. They are seeking a Senior Bioinformatics Data Engineer to build and maintain data ingestion pipelines, develop data transformations, and ensure data quality standards are met.

Responsibilities:

• Build and maintain Dagster-orchestrated ingestion pipelines for genomics vendors (Caris, Predicine, Tempus, Olink, CellCarta), including IO managers, Iceberg writers, and row-level accounting
• Develop and harden dbt Silver-to-Gold transformations: real-data test coverage, store-failures patterns, staging/intermediate/mart models, and macro consolidation
• Implement clinical data ingestion paths (SDTM and ADaM), reconciliation logic, and subject-dimension routing
• Deliver platform infrastructure: FastAPI endpoints, CI/CD pipelines, containerized deployments, observability instrumentation, and Redshift performance tuning
• Extract transformation rules from legacy R and PySpark code and reconcile against new platform implementations
• Identify repetitive processes and convert them into automated workflows, guardrails, or reusable tooling
• Participate in adversarial design and code reviews, identifying edge cases and pushing back on suboptimal patterns
• Collaborate with the lead engineer on design decisions and jointly own delivery velocity through paired working sessions and PR reviews
• Ensure all work meets reproducibility standards: CI on every PR, automated tests, no ad-hoc notebook-based production processes

Requirements:

• AI-native engineering practice: demonstrated experience building systems and workflows around AI coding agents (Claude Code, Cursor, Codex, or equivalent) - not just prompting them. You recognize when a repeated process should become an automated pipeline, when agent output needs guardrails, and when to build infrastructure that makes future work faster. Surface-level tool usage is insufficient
• Education: Bachelor's or master's degree in computer science, Data Engineering, Bioinformatics, or related field
• Experience: 5+ years of professional experience in data engineering with shipped production pipelines on AWS (S3, ECS/Fargate, Redshift or equivalent MPP)
• Strong proficiency in Python and SQL with working knowledge of modern data engineering libraries
• Advanced proficiency with dbt and a workflow orchestration tool (Dagster, Airflow, or Prefect)
• Data quality instinct: track record of catching silent failures, questioning data correctness assumptions, and noticing lossy joins or incomplete deliveries
• Solid understanding of lakehouse architecture patterns, ETL processes, and schema design for complex multi-modal datasets
• Ability to handle PHI-adjacent clinical data under Incyte's contractor policy (background check, compliance training, VPN access)
• Willingness to work within legacy codebases (R, PySpark) to extract business rules and validate new implementations
• Excellent communication skills and ability to work in an embedded pair model with tight feedback loops
• Direct experience with Apache Iceberg, AWS Glue Catalog, or lakehouse table formats
• Comfort reading genomic data (VAF, HGVS nomenclature, VCFs, CNV/fusion semantics) or demonstrated ability to ramp on unfamiliar scientific domains quickly
• Familiarity with clinical data standards including SDTM, ADaM, and CDISC
• Pharma, clinical research, or life sciences background
• Experience with containerization (Docker/ECS) and infrastructure-as-code (CloudFormation)
• Proficiency in R for interoperability with bioinformatics teams