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Senior Data Engineer

Join Doctronic as the first dedicated data engineer, owning end-to-end data processes across the organization.

Location
New York City
Compensation
$200k–$275k/yr
Level
senior
Type
full time

Posted by employer 3 weeks ago

First seen on Joblaze 1 week ago

Last verified on the company career page 1 day ago

Apply at Doctronic → Save job Scanned from doctronic.ai

AI in the day-to-day

Support the AI team's data needs for model training.

Requirements

Experience
5+ years

Not disclosed in this posting: work arrangement, visa sponsorship.

Benefits

Equity/Stock Options Parental Leave

Joblaze summary

In this role, the Senior Data Engineer at Doctronic will be responsible for managing the entire data pipeline, ensuring seamless data flow from production systems to the lakehouse and warehouse. Key skills include strong proficiency in SQL and Python, along with experience in building ELT/CDC pipelines and working with modern data stacks like S3 and Snowflake. This position is ideal for a seasoned data engineer with a background in healthcare data governance and a proactive approach to problem-solving in a flat organizational structure.

Joblaze insights

Quick facts

What's the salary range?
Doctronic lists $200,000–$275,000 for this role.
How much experience is required?
At least 5 years of relevant experience for this Senior Data Engineer role.
What's the tech stack?
Joblaze extracted these technologies from the posting: AWS, Airflow, Apache Iceberg, Dagster, Glue, IAM.
What seniority level is this role?
Doctronic targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Senior Data Engineer role at Doctronic.

From the original posting

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

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