Senior Data Engineer

The RoleYou will be Doctronic's first dedicated data engineer, and you will own the plumbing end to end: how data moves from our production systems into our lakehouse and warehouse, how it gets transformed into trusted, documented tables, and who can access what.This role serves every team in the company: AI engineering, product, finance, partnerships, and data to name a few.What You'll DoBuild reliable, monitored CDC pipelines from our production databases (MariaDB, PostgreSQL, MongoDB) into our S3 + Iceberg lake and SnowflakeStand up a transformation layer (e.g. dbt) on Snowflake so core business metrics (visits, bookings, revenue, retention) come from tested, version-controlled modelsSelect and implement an orchestration tool so pipelines and dashboard refreshes run automatically, with alerting when they breakDesign and enforce the access control model for patient data: row/column-level PHI restrictions, HIPAA Safe Harbor compliance, anonymization pipelines, and account deletion workflowsEstablish a single governed copy of production data that analytics, finance, and the AI team all read fromSupport the AI team's data needs for model trainingDesign and build a best-practice warehouse architecture with clean raw, transformed, and business-ready layers powering our executive dashboardsWhat We're Looking For5+ years of data engineering experience, including ownership of production data platforms end to endStrong SQL and Python, with experience building and operating ELT/CDC pipelines (Fivetran, Airbyte, or similar)Hands-on experience with a modern lakehouse/warehouse stack: S3, Apache Iceberg, a catalog layer, and Snowflake or an equivalent warehouseExperience with transformation frameworks (dbt or similar) and orchestration tools (Airflow, Dagster, Glue workflows, or similar)Solid AWS fundamentals: IAM, Lambda, Kinesis, GlueA pragmatic, reliability-first mindsetComfort operating with high autonomy and minimal specs in a flat, engineering-first organizationStrong communication skills; you'll work directly with product, marketing, finance, and AI stakeholdersNice to HaveExperience with HIPAA/PHI data governance, anonymization, or healthcare dataExperience with event/behavioral data pipelines (ClickHouse, GTM/server-side tracking, CDPs)Familiarity with ML data workflows: feature pipelines, training datasets, notebook environments (SageMaker, Databricks, Jupyter)Experience with BI tooling (Metabase or similar) and semantic/metrics layersPrior experience as the first or only data engineer at a startupCompensation & BenefitsBase salary range: $200,000 to $275,000 annually, depending on experience, plus meaningful equity