Technical Product Manager, Data Platform

Leap

8h•$190,000 - $230,000

About The Position

Leap is hiring a hands-on technical product manager to own the product direction and delivery of its data platform and integrations. Data supports client launches, patient identification, care coordination, drug sourcing, and savings measurement. The role brings structure to requests for Data Engineering by clarifying needs, setting priorities across teams, and communicating trade-offs. It turns prioritized work into scoped projects with milestones, dependencies, and acceptance criteria, while balancing immediate business commitments with platform investments. The position spans the ingestion engine, data quality and traceability, and integrations that embed Leap into client and partner workflows. Engineering owns architecture and implementation; the product manager defines needed capabilities and helps sequence investments. The role requires hands-on technical fluency, including querying BigQuery, interpreting Airflow DAGs and dbt models, evaluating Fivetran connectors, and investigating data issues. It works closely with Data Engineering, Platform Engineering, Analytics, Implementation, Client Success, and external technical partners, and sits within Leap’s Engineering organization.

Requirements

Experience owning technical products or programs involving data platforms, infrastructure, or integrations, such as as a technical product manager, technical program manager, solutions architect, or engineer with product ownership responsibilities.
Experience managing intake and prioritization across multiple teams with competing needs, resolving disagreements, negotiating scope, and building alignment.
Track record of taking ambiguous needs through scoping, prioritization, and delivery, including managing dependencies and making difficult trade-offs.
Strong SQL skills and sufficient fluency in Python, orchestration tools, and transformation frameworks to investigate issues and challenge technical assumptions.
Experience with cloud data warehouses such as BigQuery or Snowflake, ingestion tools such as Fivetran, and workflows using tools such as Airflow and dbt.
Experience delivering external file-based or API integrations with incomplete documentation, inconsistent data, and changing requirements.
Ability to reason about system architecture and explain how technical choices affect delivery, reliability, cost, and future capabilities.
Clear writing skills, including producing specifications engineers can build from and documentation other teams can use.
Practical experience using AI tools to accelerate analysis, technical investigation, documentation, or delivery, with sound judgment about validating outputs and handling sensitive data.

Nice To Haves

Experience with healthcare eligibility, medical or pharmacy claims, clinical data, or drug pricing.
Familiarity with healthcare data standards such as X12, NCPDP, or HL7/FHIR.
Experience working with PHI in a HIPAA-regulated environment.
Background in data, analytics, implementation, or software engineering.
Experience building reusable integration capabilities or embedding products into partner workflows.
Experience establishing product and delivery practices at an early-stage company.

Responsibilities

Own the Data Engineering intake process and provide teams a clear way to submit requests and understand prioritization decisions.
Clarify requests with stakeholders by assessing the problem, business impact, urgency, and dependencies before committing engineering capacity.
Reconcile competing needs, distinguish firm deadlines from preferred timing, make trade-offs explicit, and escalate decisions needing leadership input with options and a recommendation.
Maintain a prioritized backlog and roadmap that balance client launches, business needs, platform improvements, and reliability; communicate commitments, deferrals, and changes.
Improve intake and requirements gathering to reduce back-and-forth as the company grows.
Translate priorities into problem statements, requirements, dependencies, and measurable acceptance criteria.
Work with engineers to define project milestones, test assumptions, and establish realistic timelines.
Coordinate dependencies across teams and external partners, track delivery, surface risks, and agree on scope or timing changes with affected teams.
Validate completed work against acceptance criteria and the original business need.
Maintain an understanding of the data stack, data flows, team dependencies, and unclear ownership or capabilities.
Own product requirements for a reusable ingestion engine, including validation, normalization, error handling, and onboarding workflows.
Identify recurring manual work and one-off implementations, and prioritize shared capabilities that support growth.
Clarify business requirements for engineering-led architecture and tooling decisions, weighing delivery, reliability, cost, and future needs.
Define data provenance requirements, including data sources, transformations, usage, and ownership.
Set expectations with data consumers for freshness, completeness, and accuracy, and work with engineering on monitoring, alerting, and escalation.
Ensure sources, data contracts, ownership, and platform decisions are documented; drive recurring data quality issues toward durable resolution.
Partner with Analytics on metric lineage and with Security on access controls, PHI handling, retention, and third-party data use requirements.
Scope eligibility, claims, clinical, drug pricing, and operational data integrations, including formats, delivery methods, refresh cadences, and downstream requirements.
Partner with Implementation to make client onboarding faster and more repeatable, with clear readiness criteria and ownership.
Identify and scope opportunities to embed Leap in client and partner tools through APIs, data exchanges, and workflow integrations.
Work with external technical teams to clarify requirements, confirm dependencies, and coordinate testing and launch.
Validate integrations end to end against the needs of dependent teams and workflows.