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Salary: USD 200,000 - 275,000 / annual
Doctronic is seeking its first dedicated Data Engineer to own the complete data infrastructure and governance strategy. You will design and build reliable, monitored data pipelines that move data from production systems (MariaDB, PostgreSQL, MongoDB) into a modern lakehouse (S3 + Iceberg) and Snowflake warehouse. You'll establish a transformation layer using dbt to create tested, version-controlled models for core business metrics (visits, bookings, revenue, retention) and implement orchestration tools (Airflow, Dagster, or similar) with automated alerting.
A critical aspect of this role is designing and enforcing access controls for sensitive patient data, including row/column-level PHI restrictions, HIPAA Safe Harbor compliance, anonymization pipelines, and account deletion workflows. You will create a single governed copy of production data that serves analytics, finance, and AI teams, supporting the AI team's model training needs. You'll architect a best-practice warehouse with clean raw, transformed, and business-ready layers powering executive dashboards.
This role serves every team in the company: AI engineering, product, finance, partnerships, and data analytics. You'll work in a flat, engineering-first organization with high autonomy and minimal specs, requiring strong communication skills to collaborate directly with product, marketing, finance, and AI stakeholders.
Required: 5+ years of data engineering experience with end-to-end production data platform ownership, strong SQL and Python, hands-on ELT/CDC pipeline experience (Fivetran, Airbyte), modern lakehouse/warehouse stack proficiency (S3, Iceberg, Snowflake), transformation and orchestration frameworks, solid AWS fundamentals (IAM, Lambda, Kinesis, Glue), and pragmatic reliability-first mindset.
Nice-to-have: HIPAA/PHI data governance experience, event/behavioral data pipelines, ML data workflows, BI tooling, or prior startup data engineering experience.
