This is a fully remote position, open to applicants in United States.

📋 Description

• Develop tracking systems for product analytics, experimentation, and feature management.

• Ensure event schemas are enforced at the source.

• Create data processing systems using Bronze, Silver, and Gold layers within Databricks.

• Implement automated schema evolution, contract testing, safe backfills, freshness monitoring, and volume monitoring.

• Develop machine learning infrastructure for feature computation and serving, along with training and evaluation pipelines, and model output integration into products.

• Generate self-service templates, local development and preview environments, policy-as-code for PHI, ownership routing for alerts, and progressive deployment gates.

• Empower subject matter experts and agents to safely make alterations to data.

• Set up data contracts, continuous integration data diffing, validation gates, lineage tracking, observability, and one-command rollback functionalities.

⛳️ Requirements

• Experience in building internal platforms or infrastructures that have been adopted by other engineers.

• Proficient in operating production data or machine learning systems and participating in on-call support.

• Strong skills in Python and SQL.

• Comfortable working with Databricks and lakehouse environments; experience with Snowflake or BigQuery is also applicable.

• Proven ability to design and evolve interfaces and schemas without disrupting dependent teams.

• Experience with testing and continuous integration for data or machine learning systems.

• 1–4 years of engineering experience.

• Nice-to-have: knowledge in dbt, DLT, Dagster, Airflow, Kafka, Spark Structured Streaming, data contracts, data diffing, lineage tools, Terraform, feature stores, MLOps and evaluation tools, agentic coding workflows, as well as experience in healthcare, PHI, or HIPAA.