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.
The Senior Data Engineer is responsible for owning Leap's data infrastructure end-to-end — from ingestion pipelines and warehouse architecture to the reporting layer that drives business decisions. This role partners closely with clinical operations, business operations, and leadership to ensure that data is reliable, traceable, and ready to power both human users and AI workloads. You will own the design decisions about how the data stack is built and evolved, operating with high autonomy in a small, fast-moving engineering team.
Key ResponsibilitiesPipelines and Warehouse
Build and own data pipelines and ETL processes for claims ingestion, drug pricing, and CRM sync using BigQuery and Python
Design production pipelines for batch and streaming workloads, with a particular focus on high-volume claims data and new large-scale data sources on the roadmap
Architect warehouse schemas and transformations with clear separation between raw, staging, and modeled layers
Maintain data quality and reliability across systems that feed both human users and AI workloads, including row-count checks, schema drift detection, anomaly alerting, and silent upstream change detection
Data Governance
Design pipelines to be idempotent and replayable, with raw data always preserved to enable reprocessing when logic changes
Track data lineage across the full lifecycle — origin, transformation, and downstream dependencies
Validate data at every stage before it reaches a dashboard or AI system
Reporting Infrastructure
Build reporting systems that give sales, clinical, and leadership teams live visibility into business performance
Create automated alerting that surfaces meaningful changes in data so the team acts on insights rather than requesting them
AI-Ready Data Infrastructure
Build PHI-safe pipelines that support LLM workloads, agent systems, and automation
Design a unified data architecture that connects claims, drug pricing, patient records, CRM activity, and clinical workflows into a coherent whole
Own ingestion of external data from non-standard formats and sources across a diverse and growing provider base
Required
5+ years of experience with Python, SQL, and dbt, with hands-on expertise in BigQuery, Snowflake, or a comparable cloud data warehouse and proficiency with orchestration tools such as Airflow, Dagster, or Prefect
Demonstrated experience architecting data platforms, including decisions around batch vs. streaming, incremental vs. full-refresh, and warehouse structure
Proven ability to build monitoring, lineage tracking, and governance systems that trace data from source to report
Experience using AI tools in day-to-day work and building data infrastructure that AI systems can rely on in production
Background as an early employee or founding data engineer responsible for building a data stack from the ground up
Preferred
Healthcare or HIPAA experience; familiarity with ingestion tools such as Fivetran; CRM integrations (Salesforce, HubSpot); or prior experience building data infrastructure for LLM or AI workloads
Experience with streaming frameworks such as Kafka, Pub/Sub, or Flink, or designing systems that handle both batch and real-time data flows
Comfort with cloud infrastructure (GCP, AWS) and Linux/sysadmin fundamentals, including VM debugging, log management, and service administration
A bias toward simple, cost-effective solutions — defaulting to open-source and applying sound judgment about when managed services justify their cost 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.
Top Skills
What We Do
Leap is the industry’s only transparent specialty infusion benefit solution, enabling employers to reduce specialty drug costs by up to 60%. We replace opaque drug markups with a patient-first care model that delivers infusion services in the home or nearby, earning a 92 patient NPS. Employers see immediate, hard-dollar savings while members receive high quality, convenient care.
