BI Lead - FT - Data Analytics Engineer, MTA Solutions

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. Apply tot his job