Staff Software Engineer, Data Warehouse

About the Role

We're hiring a Staff Software Engineer to own Commure's data warehouse platform end-to-end. You'll design, build, and operate every layer of the stack:

• CDC pipelines
• Streaming transport
• Schema governance and data contracts
• Query and serving layer
• Analytics platform

The core stack today: Debezium for CDC, StarRocks as our MPP query and serving engine, and dbt for transformation and modeling. This is a hands-on IC role with broad scope.

What You'll Do

• Own the data warehouse platform end-to-end: CDC pipelines, data lake, query layer, transformation layer, and analytics-facing tooling.
• Design and operate CDC pipelines with Debezium (and Kafka, Redpanda, or equivalent) to ingest data with low latency and high fidelity.
• Architect the data lake on object storage using open table formats (Iceberg, Delta Lake, or Hudi) with Parquet, enabling both batch and streaming workloads.
• Run and scale StarRocks (or adjacent MPP/lakehouse engines) as the query and serving layer.
• Build the transformation layer with dbt: modeling standards, tests, documentation, and a semantic layer.
• Stand up orchestration (Airflow, Dagster, or similar) along with CI/CD, observability, and data-quality tooling.
• Partner with Security and Compliance on PHI/PII handling, access controls, lineage, and auditability to meet HIPAA and SOC 2 requirements.
• Set patterns and conventions: schema contracts, ingestion patterns, and self-serve tooling.

What You Have

• 6+ years of software engineering experience, with significant time building or operating data platforms at scale.
• Experience across the modern data stack: CDC, streaming (Kafka, Redpanda), data lake formats (Iceberg, Delta, Hudi), MPP/lakehouse engines (StarRocks, ClickHouse, Trino, Snowflake, Databricks), and dbt.
• Fluent in SQL, schema design, query optimization, and cost/latency trade-offs on large datasets.
• Experience running production data infrastructure (orchestration, observability, on-call, data quality, incident response).

Preferred

• Direct experience with Debezium, StarRocks, and dbt in production.
• Experience building semantic layers (dbt Semantic Layer, Cube) or data catalogs/lineage (DataHub, OpenMetadata, Amundsen).
• Experience with HIPAA-regulated data (PHI handling, de-identification, access governance).
• Experience powering AI/ML workloads: feature stores, training-set curation, embedding pipelines, or retrieval systems.
• Experience across multiple clouds (AWS, GCP, Azure), infrastructure-as-code (Terraform, Pulumi), and Kubernetes controllers.