Senior Data Platform Engineer - End-to-End Data Warehouse

Commure; Mountain View (CA); On-site; USD 190,000 - 260,000; Full time

Job summary

Commure seeks a Senior Software Engineer to own its data warehouse platform end-to-end. You will design, build, and operate all layers: CDC pipelines, data lake, query, and analytics tooling, using Debezium, StarRocks, and dbt.

You’ll run CDC pipelines, architect data lake storage, and ensure secure, scalable data pipelines. The role demands hands-on coding, architectural decisions, and close collaboration with product and analytics teams.

Qualifications

• 5+ years of software engineering experience in data platforms.
• Experience with the modern data stack: CDC, streaming, data lakes, MPP engines, and dbt.
• Fluent SQL, schema design, and optimization for large datasets.
• Production data infrastructure including orchestration, observability, and incident response.

Responsibilities

• Own the data warehouse platform end-to-end: CDC pipelines, data lake, query layer, transformation layer, and analytics tooling.
• Design and operate CDC pipelines with Debezium and a streaming backbone.
• Architect the data lake on object storage with open table formats; support batch and streaming workloads.
• Run and scale StarRocks as the query and serving layer with cost/performance trade-offs.
• Build the dbt transformation layer with standards, tests, and a semantic layer.
• Stand up orchestration (Airflow, Dagster) and CI/CD, observability, and data-quality tooling.
• Collaborate with Security/Compliance on PHI/PII handling and access controls.

Skills

Data platforms

SQL

Data engineering

Streaming

Debezium

StarRocks

dbt

Kafka

Airflow

Kubernetes

Tools

Debezium

StarRocks

dbt

Kafka

Airflow

Iceberg

Delta Lake

Job description

Commure seeks a Senior Software Engineer to own its data warehouse platform end-to-end. You will design, build, and operate all layers: CDC pipelines, data lake, query, and analytics tooling, using Debezium, StarRocks, and dbt.

You’ll run CDC pipelines, architect data lake storage, and ensure secure, scalable data pipelines. The role demands hands-on coding, architectural decisions, and close collaboration with product and analytics teams.