Data & AI Engineer

About Rapsodo

Rapsodo is a Sports Technology company with offices in the USA, Singapore, Turkey, Malaysia & Japan. We build data-driven sports analytics products used by athletes worldwide — from Major League Baseball players to golf enthusiasts — and by the coaches who train them. We are looking for team players who will help us deliver state-of-the-art solutions as part of Team Rapsodo.

Overview

As a Senior Data & AI Engineer at Rapsodo, you will own the data platform that powers analytics, reporting, and decision-making across the company — and you will drive development of the agentic workflows built on top of it. This is a data engineer's role first: the custodianship of a production-grade warehouse spanning multiple domains, a multi-layer star schema, and a BI platform serving users company-wide. On top of that foundation, you will lead the design and delivery of agentic workflows that turn trusted data into informed, reliable action.

What You’ll Do

Own and Operate the Cloud Data Platform

• Maintain cloud analytics infrastructure as code, treating the IaC repository as the source of truth for every cloud resource.
• Operate a modern data stack spanning workflow orchestration, container management, ingestion, BI, and serverless compute; lead upgrades and patches with minimal disruption.
• Operate the company-wide BI platform, including SSO integration and supporting dashboard workflows at scale.
• Optimize warehouse cost and performance through partitioning, clustering, and query tuning; set up alerting across pipelines, connectors, and scheduled queries.
• Enforce least-privilege access, rotate credentials on schedule, maintain backups, and keep warehouse documentation current.
• Act as the final word on data quality and trust — every agent, dashboard, or automated workflow built on the warehouse is only as reliable as the custodianship behind it.

Build and Evolve Data Pipelines & Integrations

• Develop transformation repositories on a multi-layer (raw → staging → curated) star schema, with incremental hash-based loading that keeps refreshes performant on very large datasets.
• Author and maintain orchestration DAGs covering ingestion, transformation, retries, scheduling, and alerting; diagnose incidents with strong root-cause discipline.
• Build and maintain ingestion for real-time and batch sources — database CDC, ERP, identity provider syncs, and SaaS connectors across e-commerce, payments, support, marketing, and marketplaces.
• Lead new ingestion projects end-to-end (e.g. product event analytics, device telemetry) and drive the design of a unified semantic layer across product, CRM, billing, marketing, and support data — the layer that both humans and agents will query against.