Senior Data Engineer - Remote Healthcare Analytics

Ambience; San Francisco (CA); Hybrid; USD 200,000 - 250,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

401(k) match

Remote-friendly

Parental leave

Off-sites

Flexible time off

Job summary

Ambience seeks a Senior Data Engineer to build and run pipelines that ingest and transform clinical and operational data, delivering trusted metrics for cross-functional teams. You will own the data trust layer, ensuring accuracy and reproducibility across our AI-driven healthcare platform.

You’ll partner with product, engineering, clinicians, and GTM to design dashboards and analytics, implement validation frameworks, and scale data infrastructure for rapid innovation in a hybrid SF setting.

Qualifications

• 5+ years in a production Data Engineering role, with hands-on Snowflake experience (data modeling, performance tuning, warehouse administration).
• Strong SQL skills and proficiency in Python; experience building ETL/ELT pipelines, data lakes, or warehouses in modern cloud environments.
• Solid grasp of data validation, schema design, and scalable architecture.
• A clear communicator who can bridge technical and non-technical teams, gather requirements, and present to cross-functional stakeholders.
• Mission-driven, thrives in a fast-paced startup environment, and takes ownership of deliverables.

Responsibilities

• Own the Trust Layer: Build and run pipelines that ingest, validate, and transform data at scale—ensuring metrics are accurate and reproducible.

Skills

SQL proficiency

Python

ETL/ELT pipelines

Data modeling

Data validation

Communication

Tools

Snowflake

dbt

Airflow

Dagster

Job description

Ambience seeks a Senior Data Engineer to build and run pipelines that ingest and transform clinical and operational data, delivering trusted metrics for cross-functional teams. You will own the data trust layer, ensuring accuracy and reproducibility across our AI-driven healthcare platform.

You’ll partner with product, engineering, clinicians, and GTM to design dashboards and analytics, implement validation frameworks, and scale data infrastructure for rapid innovation in a hybrid SF setting.