Senior Data Engineer

Founding Data Engineer AI Healthcare

The Opportunity

Our client is building an AI-powered healthcare platform designed to make high-quality care more accessible at massive scale.

Theyre now hiring their first dedicated Data Engineer to build the data foundation behind the company.

This is not a role where you inherit a mature platform and optimize around the edges.

Youll own how data moves through the business from end to end from production systems into the lakehouse and warehouse through transformation and governance and ultimately into the hands of AI product finance partnerships and leadership.

If youve wanted the opportunity to define how a company thinks about data from the ground up this is it.

What Youll Own

Build the Data Platform

• Design and operate reliable CDC and ELT pipelines from MariaDB PostgreSQL and MongoDB into S3 Apache Iceberg and Snowflake

• Create a governed trusted source of production data that the entire company can build on

• Design a scalable warehouse architecture with clean raw transformed and business-ready layers

• Implement monitoring alerting and reliability standards across the data stack

Create Trusted Business Data

• Build the transformation layer using dbt or similar tooling

• Turn raw production data into tested documented version-controlled models

• Establish trusted definitions for metrics such as:

  • Visits

  • Bookings

  • Revenue

  • Retention

  • Product engagement

• Power executive reporting and downstream analytics from a consistent source of truth

Own Orchestration & Reliability

• Select and implement the right orchestration platform for the company

• Automate pipelines transformations and dashboard refreshes

• Build monitoring and alerting so failures are caught quickly

• Establish reliability standards as the volume and complexity of the platform grows

Build Healthcare-Grade Data Governance

Youll play a critical role in determining how sensitive healthcare data is handled.

That includes:

• Row- and column-level access controls

• PHI restrictions

• HIPAA-aligned data architecture

• Safe Harbor anonymization

• Data deletion workflows

• Role-based access policies

• Secure datasets for analytics and AI use cases

The goal is to make data highly useful without compromising patient privacy or security.

Enable AI & Product Teams

• Build datasets and pipelines supporting AI model training and evaluation

• Partner with AI engineers on training data and data quality

• Support product teams with trustworthy behavioral and product data

• Help finance marketing partnerships and leadership answer important business questions without creating separate versions of the truth

What Were Looking For

• 5 years of data engineering experience

• Experience owning production data infrastructure end to end

• Strong SQL and Python

• Experience building and maintaining CDC / ELT pipelines

• Familiarity with tools such as Fivetran Airbyte or similar platforms

• Hands-on experience with modern warehouse or lakehouse architectures

• Experience with:

  • AWS S3

  • Apache Iceberg

  • Snowflake or similar data warehouses

  • Data catalogs

  • dbt or comparable transformation frameworks

• Experience with orchestration platforms such as Airflow Dagster or AWS Glue

• Strong AWS fundamentals including IAM Lambda Kinesis and Glue

• Strong understanding of production reliability and data quality

The Type of Engineer Who Thrives Here

This role is best suited for someone who:

• Likes building systems from scratch

• Doesnt need a perfectly defined roadmap before getting started

• Can evaluate tools rather than simply use whatever is already installed

• Thinks about reliability governance and maintainability from day one

• Can translate business questions into durable data models

• Communicates well with technical and non-technical stakeholders

• Wants meaningful ownership instead of narrowly scoped tickets

• Enjoys being the person people turn to when the answer starts with What does the data actually say

Particularly Relevant Experience

Experience in any of the following would be especially valuable:

• HIPAA PHI or healthcare data

• Healthcare technology

• Data anonymization and governance

• ML training datasets and feature pipelines

• SageMaker Databricks or Jupyter environments

• ClickHouse or high-volume event pipelines

• Server-side tracking CDPs or behavioral analytics

• BI tooling such as Metabase

• Semantic or metrics layers

• First data engineer or early-stage startup experience

Healthcare experience is helpful but the bigger requirement is that youve built reliable governed data infrastructure in production.

Why This Role

Youll have an unusually broad mandate.

Your work will directly influence:

• How the company measures performance

• How executives make decisions

• How AI models are trained

• How patient data is protected

• How product teams understand behavior

• How the company scales its analytics infrastructure

Instead of joining a large data organization and owning one piece of the stack youll have the opportunity to design the stack itself.

Compensation

Base Salary: $200000 $275000
Equity: Meaningful ownership based on experience and level

This is an opportunity to become the technical owner of the data foundation behind a rapidly scaling AI healthcare company.

Required Experience:

Senior IC