Data Platform Lead

Data Platform Lead

About Jump

Jump is transforming the live sports experience with an end-to-end fan engagement platform designed for sports teams and venues. Founded by e-commerce innovator Marc Lore, MLB legend Alex Rodriguez, and entrepreneur Jordy Leiser, Jump has raised $60 million from top investors. The platform unifies ticketing, merchandise, and game day operations to create a smoother, more fan-friendly experience, powering teams across the NBA, WNBA, and NWSL. Jump is a remote-first team driven by core values of trust, playing like the underdog, teamwork, and individuality.

The Role

Jump's data platform is at a pivotal stage, evolving from an internal capability to a full-fledged product powering client analytics and insights. As the Data Platform Lead, you will own the vision and execution of this scalable, multi-tenant data infrastructure, including its AI intelligence layer. You will lead and grow the data engineering team, collaborate closely with the AI engineer on agent and LLM integration, and work across Product, Engineering, and go-to-market teams to build a platform that scales. The infrastructure you build will become core to how clients run their businesses.

What You’ll Do

• Own the data platform strategy end-to-end, encompassing ingestion architecture, scalable multi-tenant data infrastructure, transformation pipelines, a modern BI layer, and platform growth as new clients and data sources are added.
• Drive the AI-on-data layer, partnering with the AI engineer to define how agents and LLMs access, query, and act on platform data, including semantic models, retrieval patterns, and in-warehouse AI primitives.
• Build and productize the integrations motion, ingesting data from diverse first- and third-party sources, turning custom work into repeatable, operable patterns.
• Lead and develop the data engineering team, managing engineers directly, setting technical direction, and raising quality standards.
• Define engineering standards for the data organization (CI/CD, testing, infra-as-code, data lineage, governance, observability) to ensure platform scalability and resilience.
• Maintain a strong hands-on presence on the warehouse and transformation layer, contributing meaningfully alongside the team.
• Partner with go-to-market teams to define client onboarding and data delivery standards and drive engineering execution against these goals.

What We’re Looking For

• 8+ years in data engineering, with at least 2 years in a leadership role, demonstrating a proven track record of managing and developing engineers.
• Strong people management instincts: clear communication, talent development, direct feedback, and building a high-performance culture.
• Hands-on experience with a modern cloud data warehouse and transformation stack (Snowflake + dbt strongly preferred; Redshift, Databricks, or BigQuery acceptable).
• Proven experience building AI on top of structured data (semantic layers, agent/LLM access patterns to warehouses, or RAG).
• Deep expertise in data ingestion at scale, including building and owning systems that pull from disparate sources into a warehouse.
• Experience building and shipping a productized, multi-tenant data offering, considering client isolation, onboarding flows, SLAs, and support.
• Solid engineering fundamentals (version control, code review, CI/CD, infra-as-code) with a bias toward repeatable standards.

Nice to Haves

• Direct Snowflake + dbt experience, and familiarity with advanced in-warehouse AI capabilities and agent-accessible data patterns.
• ML or MLOps experience (feature stores, training pipelines, model evaluation) and building tools that extract measurable value from data.
• AWS fluency (IAM, S3, Lambda, Glue).
• Experience with modern BI tooling and self-serve analytics delivery.
• Background in sports, live events, or time-series data; experience with EU data residency, GDPR, or multi-region warehouse patterns.

Attributes for Success

• Strong desire to learn and continuously build skills.
• Tenacity in tackling challenging problems and embracing fast failure for better solutions.
• Passion for using technical skills to build products that solve real problems.
• Empathy and appreciation for diverse perspectives.
• Customer-centric mindset focused on understanding problems and users.
• Innovation and passion for exploring and implementing AI technologies.

Benefits

• Remote first
• Competitive salary and equity
• Flex PTO policy
• 401(k)
• Generous medical, dental, and vision plans
• 16 weeks paid parental leave
• $1,000 reimbursement for work-from-home tech setup
• Company-paid sustainability subscription for carbon neutrality.

Compensation

• The compensation for this role is $210,000 and includes a generous equity package.