Senior Data Engineer
Location: New York, NY About the Role :
- 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
- 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
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