Software Engineer II, Data

Iambic Therapeutics, Inc•San Diego, CA

15d•Remote

About The Position

We’re seeking a Data Engineer to build and optimize data pipelines for AI model training. You’ll work with large datasets, enhance data storage, and improve Python-based workflows. Collaborating closely with ML engineers, you’ll enhance the performance of Python-based data workflows. Ideal candidates have experience with ETL systems, orchestration tools, and multi-terabyte data processing. Familiarity with AWS, Kubernetes, and data lake technologies is a plus. This role is remote, with preference for candidates on the East Coast.

Requirements

Minimum of 8 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years experience; or equivalent experience.
Proven ability to design flexible, maintainable ETL systems.
Experience with data pipeline orchestration tools such as Prefect, Airflow, Argo, Databricks, or Spark.
Understanding of the ML model lifecycle; prior work with scientific or ML workflows is a plus.
Hands-on experience with multi-terabyte scale data processing.
Familiarity with AWS; Kubernetes experience is a bonus.
Knowledge of data lake technologies such as Parquet, Iceberg, AWS Glue etc.
Strong Python software engineering skills.
Pragmatic mindset — able to evaluate tradeoffs find solutions that empower ML researchers to move quickly.

Nice To Haves

Background in bioinformatics or chemistry is a plus.

Responsibilities

Design and improve data pipelines that process large, multi-modal datasets from a variety of internal and external sources into training datasets for AI models.
Evolve our data storage layer to support analytics, schema evolution, reproducibility, and efficient data access.
Collaborate with ML engineers to improve the performance and reliability of Python-based data processing workflows.