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Flagship Pioneering

Venture capital building bioplatform companies

Lead Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeCambridge, MA, USAIn-person

About the Job

Requirements

  • At least 6 years of hands-on data engineering experience, preferably in life sciences, biotechnology, or healthcare environments.
  • Expertise in designing and operating cloud-native data architectures, particularly on AWS.
  • Advanced proficiency in Python and SQL for data manipulation, pipeline development, and system automation.
  • Extensive experience with modern frameworks and tools such as Dagster, dbt, Spark, Iceberg, Lake Formation, Athena, and Glue.
  • Strong experience with Git, continuous integration and continuous delivery (CI/CD), CDK, containerized workloads, Docker, and ECS.
  • Experience supporting structured and unstructured data, including CSV, JSON, Parquet, and imaging data.
  • Demonstrated success leading complex cross-functional projects involving technical and scientific stakeholders.
  • Practical experience using generative AI tools, such as Claude Code and GPT-based tools, to increase engineering velocity and reduce boilerplate.
  • A track record of leading complex technical initiatives under ambiguity, making explicit trade-offs, and remaining accountable for reliable operational outcomes.

Responsibilities

  • Serve as the technical lead and subject matter expert on complex data engineering projects involving interdependent systems, legacy environments, and emerging cloud-first platforms.
  • Lead implementation of data infrastructure, platforms, tools, and other data products.
  • Lead optimization and reliability of data storage solutions, including lakehouses, marts, and warehouses.
  • Implement complex backend and data integration pipelines to support data lakes, marts, and other platforms.
  • Establish and reinforce team engineering standards for testing, documentation, release management, and monitoring.
  • Lead implementations for platform observability, management, resilience, capacity, and performance.
  • Diagnose and resolve complex failures across infrastructure and data pipelines, lead incident reviews, and ensure corrective actions improve the wider system.
  • Collaborate across Infrastructure & Operations, Lab IT, Pioneering Intelligence Tech, data science, and bioinformatics teams to ensure architectural alignment, component reuse, and shared understanding of system states and dependencies.
  • Mentor junior engineers and establish engineering standards that drive excellence, reproducibility, and innovation across the team.
  • Use generative AI tools and frameworks to accelerate pipeline development, data transformation, and metadata enrichment at scale.

Desired Qualifications

  • Experience supporting bioinformatics, cheminformatics, or clinical data workflows.
  • Familiarity with scientific software and electronic lab notebooks, particularly Benchling and CDD.
  • Exposure to Agile or Scrum-based development methodologies.
  • Relevant certifications, such as AWS Solutions Architect Associate or Data Analytics Specialty.

About the Company

Flagship Pioneering

Venture capital building bioplatform companies

Flagship Pioneering funds and incubates life-sciences ventures by creating bioplatform companies, forming early-stage NewCos and helping them grow into GrowthCos. It identifies broad scientific platforms that can spawn multiple products and builds companies around those platforms to move them from inception to growth. The firm Differentiates itself by actively creating and guiding new platform-based ventures from scratch, rather than only investing in existing companies, building a diverse pipeline of category leaders. Its goal is to develop a portfolio of platform-based biotechnology and life-science companies that deliver multiple products and advance human health and sustainability.

Company size
501-1,000
Company stage
Not listed
Total funding
$11.5B
Headquarters
Cambridge, MD
Founded
2000

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