Associate Director, Data Engineer
Core
Design, implement, deploy, and maintain robust data pipelines for R&D data and metadata to support FAIR+T principles and AI-enabled discovery.
Role type
Associate Director, hands-on individual contributor data engineer
Builds
Modular, configurable, reusable data pipelines and supporting APIs/services for R&D data lifecycle
Domain
Life sciences / R&D / Data Engineering
Deliverable
production ML models
Required skills
Python, AWS (S3, Lambda, Glue, Step Functions, RDS, CloudWatch, IAM), relational databases, workflow orchestration, data processing frameworks, software engineering practices (Git, CI/CD, testing), data quality and validation, automation, AI-assisted development, coding agents (Claude Code, Codex)
Preferred skills
AI agents and orchestration (MCP, guardrails), bioinformatics/multi-omics/genomics, life sciences research environments, non-relational databases, Kubernetes, infrastructure-as-code, large datasets, statistical/ML techniques, regulated environments, mentoring
Technologies
AWS, Python, Kubernetes, Git, CI/CD, S3, Lambda, Glue, Step Functions, RDS, CloudWatch, IAM, MCP, Claude Code, Codex
Responsibilities
Design and build pipelines for ingestion, processing, transformation, validation, enrichment, and publication of R&D data; Integrate data from internal systems, lab applications, APIs, and databases; Take solutions from prototype to production deployment and monitoring; Optimize pipelines for reliability, scalability, and cost efficiency; Collaborate with scientists and stakeholders to translate requirements into technical solutions; Identify opportunities for automation and AI-enabled workflows
Seniority
Senior, hands-on IC
