Senior Data Engineer

Doctronic
New York +1 more
Hybrid

Who this role is best for

Candidates with end-to-end data platform ownership experience and comfort with HIPAA/PHI governance will find this senior data engineering role in healthcare tech, located in New York City and San Francisco, highly aligned with their background.

Best fit for

  • Candidates with end-to-end data platform ownership experience and comfort with HIPAA/PHI governance
    — “ownership of production data platforms end to end”
  • Individuals who have previously led data infrastructure at startups or scaleups
    — “Prior experience as the first or only data engineer at a startup”
  • Candidates with a strong background in building and operating CDC pipelines and transformation frameworks
    — “experience building and operating ELT/CDC pipelines”

Things to consider

  • The role requires handling HIPAA/PHI data, which involves strict compliance and anonymization protocols
    — “row/column-level PHI restrictions, HIPAA Safe Harbor compliance”
  • This is a high-impact role that serves multiple teams across the company
    — “This role serves every team in the company: AI engineering, product, finance, partnerships, and data to name a few”

How to stand out

  • Emphasize your experience in designing end-to-end data pipelines and governed data architectures
    — “Build reliable, monitored CDC pipelines from our production databases into our S3 + Iceberg lake and Snowflake”
  • Highlight your ability to implement data access controls and ensure compliance with regulations
    — “Design and enforce the access control model for patient data: row/column-level PHI restrictions, HIPAA Safe Harbor compliance”
  • Demonstrate your hands-on experience with orchestration tools like Airflow or Dagster
    — “Select and implement an orchestration tool so pipelines and dashboard refreshes run automatically”
  • Showcase your ability to work with minimal guidance in a flat, engineering-first organization
    — “Comfort operating with high autonomy and minimal specs in a flat, engineering-first organization”
Pace · SteadyCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • reliable data pipelines
  • secure data access
  • governed data warehouse
Typical background
data engineeringdata warehousingdata transformation

Skills & requirements

Required

Data EngineeringSQLPythonElt/cdc PipelinesData TransformationData Access ControlWarehouse Architecture

Preferred

Hipaa/phi Data GovernanceEvent/behavioral Data PipelinesML Data WorkflowsBI Tooling

Stack & domain

Data EngineeringSQLPythonElt/cdc PipelinesS3Apache IcebergSnowflakedbtAWSHipaa/phi Data GovernanceEvent/behavioral Data PipelinesML Data WorkflowsBI ToolingCommunicationAutonomyReliabilityPragmatismAIHealthcare

About the role

Original posting from Doctronic via Ashby

THE ROLE

You 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 DO

  • Build reliable, monitored CDC pipelines from our production databases (MariaDB, PostgreSQL, MongoDB) into our S3 + Iceberg lake and Snowflake
  • Stand up a transformation layer (e.g. dbt) on Snowflake so core business metrics (visits, bookings, revenue, retention) come from tested, version-controlled models
  • Select and implement an orchestration tool so pipelines and dashboard refreshes run automatically, with alerting when they break
  • Design and enforce the access control model for patient data: row/column-level PHI restrictions, HIPAA Safe Harbor compliance, anonymization pipelines, and account deletion workflows
  • Establish a single governed copy of production data that analytics, finance, and the AI team all read from
  • Support the AI team's data needs for model training
  • Design and build a best-practice warehouse architecture with clean raw, transformed, and business-ready layers powering our executive dashboards

WHAT WE'RE LOOKING FOR

  • 5+ years of data engineering experience, including ownership of production data platforms end to end
  • Strong 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 warehouse
  • Experience with transformation frameworks (dbt or similar) and orchestration tools (Airflow, Dagster, Glue workflows, or similar)
  • Solid AWS fundamentals: IAM, Lambda, Kinesis, Glue
  • A pragmatic, reliability-first mindset
  • Comfort operating with high autonomy and minimal specs in a flat, engineering-first organization
  • Strong communication skills; you'll work directly with product, marketing, finance, and AI stakeholders

NICE TO HAVE

  • Experience with HIPAA/PHI data governance, anonymization, or healthcare data
  • Experience 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 layers
  • Prior experience as the first or only data engineer at a startup

COMPENSATION & BENEFITS

  • Base salary range: $200,000 to $275,000 annually, depending on experience, plus meaningful equity
  • Parental Leave: 12 weeks fully paid parental leave for all parents, regardless of gender or path to parenthood — no distinction between birthing and non-birthing parent

Source: Doctronic careers (Ashby)

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