Data Platform Lead

Description Jump is transforming the live sports experience with the only end-to-end fan engagement platform built specifically for sports teams and venues. By focusing on aligned incentives between teams and fans, our platform unifies ticketing, merchandise, and game day operations - creating a smoother, more fan-friendly experience. Founded in 2021 by e-commerce innovator Marc Lore, MLB legend Alex Rodriguez, and entrepreneur Jordy Leiser, we’ve raised $60 million from top investors including Alexis Ohanian’s Seven Seven Six and Forerunner Ventures. Our platform powers teams across the NBA, WNBA, and NWSL helping them boost ticket sales and deliver innovative fan experiences. We’re a remote-first team driven by core values - begin and build with trust, play like the underdog, win as a team, and do your thing. If you’re collaborative, adaptable, and eager to shape the future of live sports, Jump is the place for you. The Role Jump's data platform is at an inflection point. What started as an internal capability now powers the analytics and insights our clients rely on every day. We're turning it into a full product: scalable, multi-tenant data infrastructure, an expanding library of integrations pulling from a growing set of first- and third-party data sources, and an AI intelligence layer that transforms raw data into actionable decisions. As Data Platform Lead, you'll own the vision and execution of that platform. You'll lead and grow our data engineering team, partner closely with our AI engineer to shape how agents and LLMs consume and act on our data, and work across Product, Engineering, and go-to-market teams to build something that scales — not a series of one-off implementations. The platform you build here will become core infrastructure for how our clients run their business. What You'll Do - Own the data platform strategy end-to-end — from ingestion architecture and scalable, multi-tenant data infrastructure to transformation pipelines, a modern BI layer, and how the platform grows as we add clients and data sources. - Drive the AI-on-data layer. Partner with our AI engineer to define how agents and LLMs access, query, and act on platform data — semantic models, retrieval patterns, and in-warehouse AI primitives. - Build and productize our integrations motion — ingesting data from a growing set of first- and third-party sources. Turn what today requires custom work into a repeatable, operable pattern. - Lead and develop our data engineering team. You'll manage directly, set technical direction, and raise the bar on quality — starting with a tight-knit team with room to grow. - Define the engineering standards for the data org — CI/CD, testing, infra-as-code, data lineage, governance, and observability — so the platform scales without fragility. - Be a strong hands-on presence on the warehouse and transformation layer — fluent enough in Snowflake to contribute meaningfully alongside the team, not just oversee it. - Partner with go-to-market teams to define what great looks like for client onboarding and data delivery, and drive engineering execution against that bar. What We're Looking For - 8+ years in data engineering, with at least 2 years in a leadership role — you have a proven track record of managing and developing engineers - Strong people management instincts: clear communicator, good at developing talent, comfortable giving direct feedback, and able to build a high-performance culture even with a small team. - Hands-on experience with a modern cloud data warehouse and transformation stack — Snowflake + dbt strongly preferred; Redshift, Databricks, or BigQuery with a fast ramp is acceptable. - Proven experience building AI on top of structured data — semantic layers, agent/LLM access patterns to warehouses, or retrieval-augmented generation. - Deep expertise in data ingestion at scale — you've built or owned the systems that pull from many disparate sources into a warehouse. You know when to use an off-the