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Senior Software Engineer, Data Platform

Pay
Pay not listedSimilar roles state $127K–$190K
Work setting
Hybrid — work setting source
Work setup in the employer’s posting: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: FullTime
From the employer’s posting

What you’ll work on

Full posting

We're hiring a Senior Software Engineer to own Commure's data warehouse platform end-to-end.

The core stack today: Debezium for CDC, StarRocks as our MPP query and serving engine, and dbt for transformation and modeling.

  • You'll design, build, and operate every layer of the stack:

  • Own the data warehouse platform end-to-end: CDC pipelines, data lake, query layer, transformation layer, and the analytics-facing tooling that sits on top.

  • Build the transformation layer with dbt: modeling standards, tests, documentation, and a semantic layer that gives every team a single source of truth for metrics.

From the employer’s posting
We're hiring a Senior Software Engineer to own Commure's data warehouse platform end-to-end. You'll design, build, and operate every layer of the stack:
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. You'll make architectural calls, write the code that matters most, and establish the patterns and conventions on the data platform.
About the Role We're hiring a Senior 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
What You'll Do Own the data warehouse platform end-to-end: CDC pipelines, data lake, query layer, transformation layer, and the analytics-facing tooling that sits on top. Design and operate CDC pipelines with Debezium (and Kafka, Redpanda, or an equivalent streaming backbone) that move data from operational databases into the warehouse with low latency and high fidelity.
Run and scale StarRocks (or adjacent MPP/lakehouse engines) as the query and serving layer - schema design, materialized views, ingestion patterns, tuning, and cost/performance trade-offs. Build the transformation layer with dbt: modeling standards, tests, documentation, and a semantic layer that gives every team a single source of truth for metrics. Stand up orchestration (Airflow, Dagster, or similar) and the CI/CD, observability, and data-quality tooling that make the platform trustworthy day-to-day.
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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 12, 2026today
Recorded sightings
1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,239 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 55.

At Commure, jobs usually come down by about day 44.

From 13,209 similar postings that came down, and 5 of Commure’s. Coming down is not always a hire.

Commure is hiring

6 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • SQL
  • AWS
  • Azure
  • ClickHouse
  • Databricks
  • dbt
  • Delta Lake
  • GCP
  • Iceberg
  • Kafka
  • Kubernetes
  • Snowflake
  • Terraform
  • Trino
  • Airflow
  • Dagster
Where the posting names them
- Experience across the modern data stack: CDC (Debezium or equivalent), streaming (Kafka, Redpanda), data lake formats (Iceberg, Delta, Hudi), an MPP or lakehouse query engine (StarRocks, ClickHouse, Trino, Snowflake, Databricks), and dbt. - Fluent in SQL, schema design, query optimization, and reasoning about cost and latency trade-offs on large datasets. - Experience running production data infrastructure (orchestration, observability, on-call, data quality, and incident response).
- 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. Please be aware that all official communication from us will come exclusively from email addresses ending in @commure.com. Any emails from other domains are not affiliated with our organization.
- 5+ years of software engineering experience, with significant time building or operating data platforms at scale. - Experience across the modern data stack: CDC (Debezium or equivalent), streaming (Kafka, Redpanda), data lake formats (Iceberg, Delta, Hudi), an MPP or lakehouse query engine (StarRocks, ClickHouse, Trino, Snowflake, Databricks), and dbt. - Fluent in SQL, schema design, query optimization, and reasoning about cost and latency trade-offs on large datasets.
- 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. You'll make architectural calls, write the code that matters most, and establish the patterns and conventions on the data platform. What You'll Do
- Run and scale StarRocks (or adjacent MPP/lakehouse engines) as the query and serving layer - schema design, materialized views, ingestion patterns, tuning, and cost/performance trade-offs. - Build the transformation layer with dbt: modeling standards, tests, documentation, and a semantic layer that gives every team a single source of truth for metrics. - Stand up orchestration (Airflow, Dagster, or similar) and the CI/CD, observability, and data-quality tooling that make the platform trustworthy day-to-day.
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).
- 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, and access governance).
- Design and operate CDC pipelines with Debezium (and Kafka, Redpanda, or an equivalent streaming backbone) that move data from operational databases into the warehouse with low latency and high fidelity. - Architect the data lake on object storage using an open table format (Iceberg, Delta Lake, or Hudi) with Parquet, enabling both batch and streaming workloads and clean separation of storage from compute. - Run and scale StarRocks (or adjacent MPP/lakehouse engines) as the query and serving layer - schema design, materialized views, ingestion patterns, tuning, and cost/performance trade-offs.
- Own the data warehouse platform end-to-end: CDC pipelines, data lake, query layer, transformation layer, and the analytics-facing tooling that sits on top. - Design and operate CDC pipelines with Debezium (and Kafka, Redpanda, or an equivalent streaming backbone) that move data from operational databases into the warehouse with low latency and high fidelity. - Architect the data lake on object storage using an open table format (Iceberg, Delta Lake, or Hudi) with Parquet, enabling both batch and streaming workloads and clean separation of storage from compute.
- Build the transformation layer with dbt: modeling standards, tests, documentation, and a semantic layer that gives every team a single source of truth for metrics. - Stand up orchestration (Airflow, Dagster, or similar) and the CI/CD, observability, and data-quality tooling that make the platform trustworthy day-to-day. - Partner with Security and Compliance on PHI/PII handling, access controls, lineage, and auditability so the platform meets HIPAA and SOC 2 bar by default.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

At Commure, we're building the AI Operating System for healthcare, the foundation that defines how care is delivered, documented, and financed. Our platform spans the full care journey: Ambient AI and Dictation eliminating documentation burden at the point of care, intelligent Agents automating patient and revenue workflows, and autonomous RCM processing billions in claims, all on a single AI-native platform integrated with 60+ EHRs.

Healthcare carries a $1 trillion administrative burden and we're at the center of transforming it. Today, 500,000+ clinicians across 500+ healthcare organizations nationwide trust Commure to handle $25B+ in annual claims and support over 200 million patient interactions. Our latest $70M raise at a $7B valuation reflects the confidence the market has placed in this mission. We've also been named to the Fortune Future 50 list and the 2026 AI Breakthrough Awards for “Overall NLP Company of the Year.”

Our team works directly alongside clinicians, not through layers of process, which means the gap between what you build and its impact on patient care is immediate. We move fast, deploy daily, and take full ownership from early thinking to production. If you're energized by hard problems, high stakes, and a team that holds itself to a high bar, you'll find your people here.

The future of healthcare is being built right now. Come deliver this transformation.

About the Role

We're hiring a Senior 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. You'll make architectural calls, write the code that matters most, and establish the patterns and conventions on the data platform.

What You'll Do

  • Own the data warehouse platform end-to-end: CDC pipelines, data lake, query layer, transformation layer, and the analytics-facing tooling that sits on top.

  • Design and operate CDC pipelines with Debezium (and Kafka, Redpanda, or an equivalent streaming backbone) that move data from operational databases into the warehouse with low latency and high fidelity.

  • Architect the data lake on object storage using an open table format (Iceberg, Delta Lake, or Hudi) with Parquet, enabling both batch and streaming workloads and clean separation of storage from compute.

  • Run and scale StarRocks (or adjacent MPP/lakehouse engines) as the query and serving layer - schema design, materialized views, ingestion patterns, tuning, and cost/performance trade-offs.

  • Build the transformation layer with dbt: modeling standards, tests, documentation, and a semantic layer that gives every team a single source of truth for metrics.

  • Stand up orchestration (Airflow, Dagster, or similar) and the CI/CD, observability, and data-quality tooling that make the platform trustworthy day-to-day.

  • Partner with Security and Compliance on PHI/PII handling, access controls, lineage, and auditability so the platform meets HIPAA and SOC 2 bar by default.

  • Collaborate with product and analytics teams on schema contracts, ingestion patterns, and self-serve tooling so they can build on the platform with confidence.

What You Have

  • 5+ years of software engineering experience, with significant time building or operating data platforms at scale.

  • Experience across the modern data stack: CDC (Debezium or equivalent), streaming (Kafka, Redpanda), data lake formats (Iceberg, Delta, Hudi), an MPP or lakehouse query engine (StarRocks, ClickHouse, Trino, Snowflake, Databricks), and dbt.

  • Fluent in SQL, schema design, query optimization, and reasoning about cost and latency trade-offs on large datasets.

  • Experience running production data infrastructure (orchestration, observability, on-call, data quality, and 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, and 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.

Please be aware that all official communication from us will come exclusively from email addresses ending in @commure.com. Any emails from other domains are not affiliated with our organization.


Employees will act in accordance with the organization’s information security policies, to include but not limited to protecting assets from unauthorized access, disclosure, modification, destruction or interference nor execute particular security processes or activities. Employees will report to the information security office any confirmed or potential events or other risks to the organization. Employees will be required to attest to these requirements upon hire and on an annual basis.

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