Data Infrastructure Engineer

Required :

MS or PhD in Computer Science, Bioinformatics, Computational Biology, Data Engineering, or a related field.

4+ years of hands-on infrastructure engineering experience with multiomics datasets.

Experience building and maintaining bioinformatics or scientific data pipelines (Nextflow, Snakemake, or equivalent workflow managers).

Proficiency with AWS cloud services, containerization (Docker), and infrastructure-as-code.

Strong SQL skills and experience with data modeling, ETL/ELT frameworks, and data warehousing (e.g., PostgreSQL, DuckDB, BigQuery, or Snowflake).

Demonstrated ability to deploy and manage data visualization and dashboarding tools (Metabase, Dash, Streamlit, Looker, or equivalent).

Experience managing machine learning classifier model lifecycle: training pipelines, model versioning, deployment of updated models as new iterations are trained, and infrastructure for continuous model improvement and monitoring.

Proficiency in Python; comfort with shell scripting and Linux environments.

Nice to have :

Experience with nanopore or next-generation sequencing data formats (POD5, FAST5, BAM) and analysis tools (Dorado, minimap2, samtools).

Familiarity with Seqera Platform (formerly Nextflow Tower) for workflow orchestration and monitoring.

Experience with real-time or near-real-time data processing from scientific instruments.

Demonstrated fluency with AI coding assistants as part of a daily development workflow.

Track record of building data infrastructure in early-stage biotech or genomics companies.

We’re looking for a teammate that :

Navigates complex team dynamics, partnerships, and challenges with creativity and logic.

Operates with adaptability, urgency, and flexibility in evolving environments, thriving in ambiguity.

Drives work forward without needing to be asked, taking responsibility for outcomes rather than tasks.

Treats obstacles as problems to be creatively solved, not reasons something can’t be done.

Applies sound judgment to the best available information, testing, learning, and iterating.

Shares early and directly when assumptions change, results are unclear, or timelines are at risk.

Work environment :

Collaborative culture where your ideas and expertise are valued

Direct impact on product development and company direction

Professional growth :

Work on groundbreaking next-generation proteomics technology and its data infrastructure challenges

Establish foundational data engineering architecture as the organization scales

Compensation

Estimated Base Salary $135,300-$178,350

This is the pay range for this position that we reasonably expect to pay. Individual compensation is based on various factors including, experience, education, skillset, and geographic location. This range is for the SF Bay Area, California location and may be adjusted to the labor market in other geographic areas.