
Data Engineer at SumerSports
AI-driven roster analytics for pro and NCAA teams, within salary caps.
Build and operate data pipelines powering deep learning, video, and LLM systems across multiple sports; own ingestion, transformation, orchestration, data quality, lineage, and cost/performance optimization; support batch and streaming workloads; build retrieval pipelines for AI apps over structured and unstructured data; partner closely with MLOps and sports data teams; 3–8 years in production data engineering/ETL required; must: Python, SQL, big-data frameworks, orchestration tools, data modeling/warehousing, lakehouse architectures, CI/CD/IaC, cloud and containers, exposure to LLM-powered data tools; bonus: sports/telemetry/sensor pipelines, streaming/event-driven systems, football domain knowledge, governance/observability tools, semantic layers, MLOps practices
Remote US or Canada









