BI Lead – Data Analytics Engineer - MTA

Location: Remote (US-based preferred)
Team: Data / Growth / Engineering
Reports to: Head of Marketing & Data

About Us

We’re building the future of healthcare intelligence. Our platform powers multi-touch attribution (MTA) and advanced analytics on top of a modern Python/FastAPI backend. To support our next phase of scale, we’re building a new data lake and BI stack from the ground up—designed for speed, compliance, and scalability.

We need a BI Lead / Data Analytics Engineer who is excited to architect, build, and operationalize this foundation while driving attribution insights and analytics excellence across the company.

The Role

This is a hands-on, build-from-scratch role. You’ll architect and implement the company’s first data lake, ingestion frameworks, and attribution pipelines, and scale them into a robust BI environment.

The ideal candidate is a seasoned data engineer with 7+ years of experience building enterprise-grade data platforms, but is eager to adopt and master our Python/async/FastAPI/Celery environment.

You’ll partner closely with marketing, product, and engineering to ensure our data infrastructure not only works but drives real business outcomes.

Responsibilities

• Architect & Build a Data Lake

  • Design and implement the company’s first centralized data lake to unify raw, structured, and semi-structured data.

  • Define ingestion patterns for streaming and batch pipelines across internal apps, SaaS tools, and APIs (ad platforms, CRM, telehealth systems, etc.).

• MTA & Attribution Models

  • Build pipelines that support advanced multi-touch attribution models (rule-based, probabilistic, and ML-driven).

  • Deliver accurate, timely, and explainable attribution outputs to support marketing spend decisions.

• Data Engineering & Pipelines

  • Own ETL/ELT frameworks using Python, SQL, and orchestration tools.

  • Deploy workflows in a FastAPI + Celery async task environment.

• BI & Analytics Enablement

  • Define schemas and data models that feed dashboards, experimentation, and decision-making.

  • Enable self-service analytics for marketing, product, and finance teams.

• Governance & Standards

  • Define data contracts, quality checks, documentation, and access control to keep the platform trustworthy and compliant.

• Scale & Optimize

  • Continuously improve cost efficiency, performance, and observability of the data stack.
    

Requirements

• 7+ years in data engineering, analytics, or BI roles.

• Strong experience designing and implementing data lakes or warehouses from scratch.

• Expertise with SQL and modern data warehouse/lakehouse technologies (Snowflake, BigQuery, Redshift, Delta Lake, etc.).

• Strong Python engineering skills, or proven willingness to quickly ramp into Python async patterns, FastAPI, and Celery-based architectures.

• Experience with ETL/ELT frameworks, pipeline orchestration, and API-based ingestion.

• Familiarity with attribution, experimentation, or marketing analytics concepts.

• Excellent communicator with ability to bridge technical and business teams.

Nice-to-Haves

• Exposure to marketing/healthcare data ecosystems (GA4, Freshpaint, Braze, ad platforms, EHRs).

• Hands-on experience with distributed computing frameworks (Spark, Dask, etc.).

• Experience leading a small team or mentoring junior engineers.

• Familiarity with HIPAA or other regulated environments.
  

Why Join Us

• Lead the end-to-end build of a greenfield data lake and BI environment.

• Tackle one of the hardest problems in healthcare tech: attribution and compliance at scale.

• High-impact role where your architecture decisions will shape the company for years.

Grow alongside a world-class engineering and growth team, with direct exposure to cutting-edge backend and marketing systems.