Counsel Health is a company focused on revolutionizing AI + human healthcare. They are seeking a talented Senior Data Engineer to architect and maintain the data infrastructure that supports their Clinical, AI, Product, and Financial Operations, ensuring scalability and reliability for large healthcare clients.
Responsibilities:
- Primarily focus on architecting our data infrastructure layer that drives our 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 our 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 such as NLP, embeddings, knowledge graphs, and retrieval-augmented generation
- Financial workflows for accounting tracking and observability
- Clinical and support workflows that allow non-technical teams to self-service data
- Build real-time PHI-scrubbed operational dashboards to support clinical and support teams; allowing non-technical users to self-service data using AI-supported tooling
- Set up change data capture (CDC) to store historical data and allow engineers and analysts to time travel back to a past state of the system
- Build reverse ETL infrastructure to bring analytically derived data into our core application to drive patient engagement
- Improve our financial modeling, marketing data analysis, customer acquisition and user retention metrics
- Analyze our LLM performance & latency metrics and model how this impacts costs, user experience, and potential caching strategies
Requirements:
- 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
- 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 our 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