Senior/Principal Data Engineer (CONTRACT)

Addition Therapeutics • South San Francisco, CA

4d • $95 - $100 • Onsite

About The Position

We’re looking for a Senior or Principal Data Engineer to design and implement the data infrastructure and systems that will power our data-driven discovery. You’ll play a defining role in how data is collected, organized, and made usable across the company. The ideal candidate will possess significant experience with developing data management systems and solutions in an early stage biotech environment. They will be highly collaborative and resourceful, with a keen interest in laying solid data foundations for future growth. This role has great potential to grow with the company, both technically and in scope of impact, and can contribute to paving the way for novel therapeutics that could redefine the landscape of genetic medicine. This role requires onsite presence at least 4 days per week.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in data engineering including time spent in a biotech R&D environment with a commitment to FAIR data practices.
• Proven experience designing and maintaining ETL/ELT pipelines and cloud data architectures (e.g., AWS S3, Redshift, GCP BigQuery, Snowflake).
• Proficiency in Python and SQL, and familiarity with tools such as dbt, Airflow, or Prefect.
• Understanding of data modeling and best practices for structured and unstructured data.
• Comfort working in a small, fast-moving company with minimal existing infrastructure.
• Familiarity with modern development best practices - version control, testing, CI/CD, monitoring, and incident response.
• A collaborative mindset — excited to partner with scientists, data scientists, and leadership.

Nice To Haves

• Experience with omics data, LIMS systems (Benchling), or scientific data management.

Responsibilities

• Data Infrastructure Management: design, develop, and maintain data repositories.
• Data Pipeline Development: build and maintain scalable data pipelines that extract, transform, and load (ETL) data from diverse sources.
• Data Quality & Governance: ensure data accuracy, consistency, and reliability, and implement policies for data security and privacy.
• System Monitoring & Optimization: monitor system performance, troubleshoot issues, and implement optimizations to improve the efficiency and reliability of data systems.
• Collaboration: work closely with experimentalists to understand how data is generated, and with data scientists to understand that data is used - and then create data management solutions that are fit-for-purpose for both.

What This Job Offers

• Career Level: Senior