Lead Bioinformatics Engineer

Flagship Pioneering, Inc.•Cambridge, MA

1d•$128,000 - $176,000

About The Position

Flagship Pioneering is seeking a Bioinformatics Engineer to join the Scientific Cloud team within Flagship IT. This is a high-impact individual contributor role reporting into the Director, Scientific Cloud Engineering, embedded within the sub-team. The Bioinformatics Engineer will own and operate Flagship's bioinformatics platform stack, build reusable pipeline frameworks that portfolio companies can deploy on their own, and serve as the critical bridge between Pioneering Intelligence's open-source bioinformatics library and the scientific teams across Flagship's portfolio who need to put that code to work. Equally important, t— including UK Biobank, the Francis Crick Institute, dbGaP, and similar curated dataset providers — ensuring that Flagship scientists and portfolio companies have timely, compliant access to the world's highest-quality biological data resources. This role is designed around platform ownership and enablement, not bespoke consulting. The ideal candidate is technically deep, organizationally savvy, and equally comfortable building production-grade infrastructure and coaching scientific teams to use it independently.

Requirements

M.S. or Ph.D. in Bioinformatics, Computational Biology, Genomics, Computer Science, or a closely related field.
7+ years of hands-on bioinformatics engineering experience, including production-grade pipeline development and deployment.
Deep expertise in genomic data types and file formats (FASTQ, BAM/CRAM, VCF, BED, HDF5, AnnData, etc.) and the computational tools used to process them.
Demonstrated experience building and operating cloud-native bioinformatics workflows (AWS preferred; Azure or GCP acceptable) using workflow managers such as Nextflow, Snakemake, or WDL.
Strong programming proficiency in Python and/or R, with experience in shell scripting for pipeline automation.
Familiarity with public genomic data repositories and the access/compliance frameworks that govern them (e.g., dbGaP, UK Biobank, TCGA).
Proven ability to manage complex external relationships and data access processes, including DUAs, DAC applications, and compliance reporting.
Strong communication skills and a collaborative working style; comfortable engaging with both scientific and technical audiences.

Nice To Haves

Experience administering or deploying managed bioinformatics platforms such as CodeOcean, Sequera / Nextflow Tower, Tamarind.bio, or similar cloud-native workflow environments.
Experience working in a multi-company or portfolio environment, supporting diverse scientific teams with varying computational needs.
Familiarity with single-cell omics platforms (10x Genomics, Seurat, Scanpy, scVelo) and spatial transcriptomics workflows.
Experience with containerization (Docker, Singularity) and container orchestration for HPC/cloud hybrid environments.
Knowledge of data governance frameworks, catalog tools (e.g., DataHub, Collibra), and lineage tracking as applied to scientific data.
Experience contributing to or maintaining open-source bioinformatics libraries or shared code repositories.
Prior experience in a biotechnology, pharmaceutical, or life sciences technology organization.

Responsibilities

Own and operate Flagship's portfolio bioinformatics platform stack — including CodeOcean, Sequera (Nextflow Tower), Tamarind.bio, and adjacent tools — serving as the primary administrator, configurator, and first point of escalation for platform-level issues.
Build and maintain a library of reusable, production-quality pipeline templates and starter deployments that portfolio companies and Pioneering Medicines teams can adopt without requiring bespoke engineering for each use case.
Serve as the technical bridge between Pioneering Intelligence's open-source bioinformatics library and portfolio company end users — translating contributed code into deployable, documented workflows that scientists and informatics teams can operate independently.
Establish and maintain standards for bioinformatics data formats, pipeline documentation, and code contribution guidelines, ensuring that both internally developed and PI-contributed workflows meet a consistent bar for reproducibility and portability.
Guide portfolio company scientists and informatics teams in building and adapting pipelines on their own within the platform framework; the goal is scientific self-sufficiency at the company level, not long-term pipeline ownership by Scientific Cloud.
Partner with Scientific Cloud Engineering to ensure bioinformatics platform infrastructure aligns with enterprise cloud architecture standards, including identity management, security controls, and cost governance.
Serve as Flagship's primary with external genomic and biomedical data consortia and repositories, including but not limited to UK Biobank, the Francis Crick Institute, dbGaP, GTEx, ENCODE, and other curated dataset providers.
Manage the full lifecycle of data access agreements — including Data Access Committee (DAC) applications, DUAs, renewals, and compliance reporting — in coordination with Flagship's legal and compliance teams.
Monitor the roadmaps and emerging datasets of key consortium partners, proactively surfacing new data access opportunities aligned to portfolio scientific needs.
Coordinate onboarding of new consortium-sourced datasets into Flagship's data environment, working with data engineering teammates to ensure proper ingestion, governance metadata, and access controls.
Build relationships with data operations and scientific leads at partner institutions to streamline access processes and deepen collaboration over time.
Work closely with Data & Informatics Engineering teammates — including data architects, data engineers, and software engineers — to ensure bioinformatics workloads are integrated into shared data platforms, pipelines, and catalogs.
Collaborate with Research Systems, Lab Systems, and informatics counterparts across Flagship and portfolio companies to understand scientific requirements and translate them into platform capabilities.
Partner with Pioneering Intelligence (PI) data science and machine learning teams to ensure that processed omics datasets are properly formatted, annotated, and accessible for downstream analytical and AI workflows.
Participate in cross-team technical reviews, architecture discussions, and sprint ceremonies as a contributing member of the Scientific Cloud team.
Contribute to the development of shared standards, playbooks, and documentation that benefit the broader Scientific Cloud organization and portfolio.
Act as an internal subject matter expert on genomics, transcriptomics, and multi-omics data ecosystems; advise portfolio company scientists and IT counterparts on best practices.
Evaluate and recommend appropriate computational resources (HPC, cloud batch, spot instances) for large-scale genomic workloads.
Stay current with advances in bioinformatics tooling, reference datasets, and public database standards, contributing to ongoing platform evolution.
Contribute to technical documentation, onboarding materials, and knowledge-sharing forums to build institutional bioinformatics capability over time.