Senior Data Engineer at Leap

About Leap Leap is one of the fastest-growing benefits solutions and a category-defining pioneer in employer specialty pharmacy. We are reshaping how life-changing therapies are delivered and financed, ensuring patients get the treatment they need while employers finally get a fair deal. Specialty drugs and infusions represent nearly 10% of all healthcare spend and are the fastest-growing cost category for employers. Leap tackles this challenge with a novel approach: eliminating hidden markups, expanding access to high-quality infusion providers, and bringing clarity and fairness to how therapies are priced and paid for. We’re proud to partner with numerous Fortune 500 companies and leading TPAs. Each patient we serve creates immediate ROI: lower costs, improved access, and better care. Join us as we redefine what’s possible in specialty care. ABOUT THE ROLE You'll own the pipelines, the warehouse, and the reporting layer. We want someone who builds reliable infrastructure that the rest of the company can depend on. You'll report to the engineering lead and work directly with clinical ops, business operations, and leadership. Small engineering team, high ownership. KEY RESPONSIBILITIES Pipelines and Warehouse - Build and own data pipelines and ETL for claims ingestion, drug pricing, and CRM sync (BigQuery, Python) - Design warehouse schemas and transforms that the rest of the company depends on - Maintain data quality and reliability across systems that feed both human users and AI workloads — this means row-count checks, schema drift detection, anomaly alerting, and knowing when upstream sources have silently changed, not just whether the job ran Reporting Infrastructure - Build reporting systems that give sales, clinical, and leadership teams live visibility into the business - Create automated alerting that surfaces when something has changed, so the team acts on data instead of asking for it AI-Ready Data Infrastructure - Build PHI-safe pipelines that feed LLM workloads, agent systems, and automation - Design data architecture that connects claims, drug pricing, patient records, CRM activity, and clinical workflows into a usable whole - Own the ingestion of external data from non-standard formats and sources — we work with many providers who each send data differently, and new sources are added regularly QUALIFICATIONS Required - Python, SQL, and dbt. You've worked with BigQuery, Snowflake, or a similar cloud warehouse and know your way around orchestration tools (Airflow, Dagster, Prefect, or similar). - You've built pipelines that other people depend on. Your schemas are clean and your data models are well-documented. - You use AI tools in your own work and you know how to build data infrastructure that AI systems can rely on in production. - You've been an early employee, a solo data person, or the one who built the data stack from scratch. Preferred - Healthcare or HIPAA experience, Fivetran or similar ingestion tools, CRM integrations (Salesforce, HubSpot), or experience building data infrastructure for LLM/AI workloads - Comfort with cloud infrastructure (GCP, AWS) or Linux/sysadmin fundamentals — you can debug a VM, read logs, and manage services, not just write SQL - A bias toward simple, cost-effective solutions — you reach for open-source first and know when a managed service is worth the price and lock-in At Leap, we’re building an outlier company with real impact — and that takes focus, energy, and commitment. If that excites you, we’d love to hear from you. Leap is an equal opportunity employer and welcomes applicants from all backgrounds. We’re committed to building a team that reflects a diversity of perspectives, experiences, and identities.