Counsel Health is hiring a Senior Data Engineer to own and architect the core data infrastructure powering our Clinical, AI, Product, and Financial Operations. This central role ensures our platform can scale seamlessly to meet the demands of large healthcare clients while reliably serving hundreds of thousands of patients.

What You'll Do

Architect the data infrastructure layer that drives financial, clinical, and AI applications.
Build robust batch and streaming ingestion pipelines that unify data from diverse internal and external systems into a consistent, ontology-driven data model.
Maintain dbt-driven SQL models that unify datasets from product, integrations, financial operations and clinical data, leveraging ontologies (e.g. SNOMED CT, ICD, HL7 FHIR).
Design data pipelines that handle diverse sets of structured (e.g. SQL, APIs) and unstructured (e.g., documents, notes, embeddings) datasets.
Future-proof the data platform to anticipate and support evolving needs including AI workflows, financial workflows, and clinical workflows.
Build real-time PHI-scrubbed operational dashboards to support clinical and support teams.
Set up change data capture (CDC) to store historical data and allow time travel to past system states.
Build reverse ETL infrastructure to bring analytically derived data into the core application to drive patient engagement.
Improve financial modeling, marketing data analysis, customer acquisition and user retention metrics.
Analyze LLM performance & latency metrics and model impacts on costs, user experience, and caching strategies.

What We're Looking For

5+ years of experience in data engineering building high-performance data pipelines.
Previously pioneered self-service analytics & business intelligence tooling (e.g. Hex, Sigma, Looker) for a diverse set of stakeholders.
Operational experience with data storage platforms (e.g. Databricks, Iceberg, or Snowflake) and analytical query engines (e.g. Athena or Presto).
Managed job orchestration (e.g. Dagster, Airflow) and semantic data modeling (dbt, SQL).
2+ years working in highly regulated industries such as healthcare or financial services.
Implemented row-level security and data masking for PHI/PII use cases.
Deep familiarity with row and columnar data warehouses (e.g. PostgreSQL, BigQuery, Snowflake).
Opinionated about data architecture, data modeling, and analytics in a fast-growing environment.

Nice to Have

Hands-on experience architecting data platforms from day 0 in a fast-paced, high-growth environment.
Extensively worked with healthcare data and standards (e.g. HL7 FHIR, CDS, ICD-10).
Experience with tech stack: AWS, Google Cloud, PostgreSQL, FHIR servers.
Consider yourself a Swiss-army knife data engineer who can flex into both data infrastructure, semantic modeling, and operational analytics.
Knowledge of medical statistics and are keen to learn more.
Comfortable working across teams on multi-stakeholder projects.
Thrive on working alongside exceptional teammates and derive energy from collaborative environments.

Technical Stack

Cloud: AWS, Google Cloud
Databases & Storage: PostgreSQL, FHIR servers, Databricks, Iceberg, Snowflake, BigQuery
Query Engines: Athena, Presto
Orchestration & Modeling: dbt, Dagster, Airflow