Senior Data Engineer

Doctronic; New York (NY); On-site; USD 200,000 - 275,000; Full time

Benefits offered by this job

Parental leave

Meaningful equity

Job summary

Doctronic is seeking its first dedicated data engineer to own the data plumbing from production systems to the lakehouse and warehouse. You will transform data into trusted, documented tables and control access for PHI data.

The role serves multiple teams, including AI engineering, product, finance, and partnerships, and requires 5+ years of data engineering with strong SQL, Python, and AWS fundamentals. You will build CDC pipelines and a dbt-based transformation layer in a largely autonomous,

Qualifications

• 5+ years of data engineering experience, owning production data platforms end to end.
• Strong SQL and Python, with experience building ELT/CDC pipelines (Fivetran, Airbyte, or similar).
• Hands-on with lakehouse/warehouse stacks: S3, Apache Iceberg, a catalog layer, Snowflake or equivalent.
• Experience with transformation frameworks (dbt) and orchestration tools (Airflow, Dagster, Glue).
• Solid AWS fundamentals: IAM, Lambda, Kinesis, Glue.
• Reliability-first mindset and ability to operate with autonomy.
• Strong communication to work with product, marketing, finance, and AI stakeholders.

Responsibilities

• Own end-to-end data plumbing from production systems to lakehouse and warehouse.
• Build and monitor CDC pipelines into S3 + Iceberg lake and Snowflake.
• Stand up a transformation layer (dbt) to produce core metrics.
• Select and implement orchestration for automated pipelines with alerts.
• Design access controls for PHI, HIPAA Safe Harbor, and anonymization pipelines.
• Establish a single governed production data copy for analytics, finance, and AI.
• Support AI teams with data for model training.
• Design a best-practice warehouse with clean raw, transformed, and business layers.

Skills

SQL

Python

ELT/CDC pipelines

Communication

Autonomy

Tools

Fivetran

Airbyte

dbt

Airflow

Dagster

Snowflake

S3

Apache Iceberg

Kinesis

Lambda

Glue

Job description

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