Data Platform Lead

Job not on LinkedIn

🕒 June 4

🇺🇸 United States – Remote

💵 $210k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Jump

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

⚽ Sports

☁️ SaaS

🤝 B2B

Sports • SaaS • B2B

Jump is a company that offers an end-to-end fan experience platform specifically designed for sports teams and their fans. It helps sports clubs grow revenue by nurturing lifelong relationships with fans through software solutions that include primary ticketing and fan engagement apps. Jump's solutions are designed in collaboration with over 70 professional sports teams from major leagues such as the NBA, NHL, NFL, MLS, and MLB. They offer tools to manage event inventory and access control, providing a seamless and personalized fan experience to increase fan engagement, attendance, and revenue for sports teams.

📋 Description

• 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.

🎯 Requirements

• 8+ years in data engineering, with at least 2 years in a leadership role • 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-shelf connector, when to build, and how to make either one operable at scale. • Experience building and shipping a productized, multi-tenant data offering — client isolation, onboarding flows, SLAs, and ongoing support. You think in products, not projects. • Solid engineering fundamentals: version control, code review, CI/CD, infra-as-code — and a bias toward standards that teams can repeat, not heroics that only you can maintain.

🏖️ Benefits

• Remote first • Competitive salary and equity • Flex PTO policy • 401(k) • Generous medical, dental and vision plans • 16 weeks paid parental leave for primary and secondary caregivers • $1,000 reimbursement for work-from-home tech setup • Company-paid sustainability subscription to ensure carbon neutrality is maintained for employee activities, such as travel