
11 - 50 employees
Founded 2022
⚽ Sports
🤖 Artificial Intelligence
☁️ SaaS
Sports • Artificial Intelligence • SaaS
SumerSports is an AI-powered sports analytics and technology company focused on football (NFL and NCAA). Combining over 500 years of NFL experience with machine learning, SumerSports offers products such as SūmerBrain for film retrieval and multi-layered data, SūmerLive for game tracking, SūmerNFL and SūmerNCAA for roster building and team optimization, and a player-verified metrics and talent exposure platform. The company produces draft guides, analytics-driven content with former scouts and Hall of Famers, and tools that serve players, teams, and fans to improve scouting, roster decisions, and performance evaluation.
🔥 7 minutes ago
🇺🇸 United States – Remote
💵 $160k - $190k / year
⏰ Full Time
🟡 Mid-level
🟠 Senior
🚰 Data Engineer
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11 - 50 employees
Founded 2022
⚽ Sports
🤖 Artificial Intelligence
☁️ SaaS
Sports • Artificial Intelligence • SaaS
SumerSports is an AI-powered sports analytics and technology company focused on football (NFL and NCAA). Combining over 500 years of NFL experience with machine learning, SumerSports offers products such as SūmerBrain for film retrieval and multi-layered data, SūmerLive for game tracking, SūmerNFL and SūmerNCAA for roster building and team optimization, and a player-verified metrics and talent exposure platform. The company produces draft guides, analytics-driven content with former scouts and Hall of Famers, and tools that serve players, teams, and fans to improve scouting, roster decisions, and performance evaluation.
• Design, build, and maintain data pipelines powering deep learning, video, and LLM systems • Build and operate robust pipelines for data ingestion, cleaning, and transformation using Databricks, Airflow, or Kubernetes • Develop ETL/ELT workflows in Python and SQL for batch and streaming workloads • Partner with ML/AI teams to make datasets and tools discoverable and safe for autonomous agents, including evaluation and guardrails for AI-generated queries • Develop retrieval pipelines using RAG and vector search over structured statistics and unstructured sources such as scouting notes and video metadata • Model and maintain structured data assets in Delta, Parquet, and Iceberg formats for reliability, versioning, and lineage tracking • Implement orchestration and monitoring by scheduling jobs, tracking dependencies, and automating recovery from failures • Ensure data quality and compliance through validation frameworks, schema enforcement, and audit logging • Contribute to data platform evolution by evaluating tools, standardizing best practices, and improving developer experience • Support performance and cost optimization across compute, storage, and orchestration systems • Collaborate with MLOps and Sports Data teams to integrate data and AI across multiple sports
• 3–8 years of experience as a Data Engineer or ETL Developer in a production environment • Proficiency in Python and SQL • Strong familiarity with Databricks, Spark, or equivalent big-data frameworks • Experience with workflow orchestration tools such as Airflow, Dagster, Luigi or Prefect • Deep understanding of data modeling, data warehousing, and distributed data processing • Knowledge of modern data lakehouse architectures • Familiarity with CI/CD, GitHub Actions, Infrastructure as Code, and data pipeline testing frameworks • Comfort working in a cross-functional environment with ML, product, and analytics teams • Exposure to LLM-powered data tools: text-to-SQL, RAG, agent/tool interfaces (e.g. MCP), or natural-language analytics • Previous work with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Docker, Kubernetes) • Preferred: Previous experience with sports, telemetry, or sensor data pipelines • Preferred: Familiarity with streaming frameworks and event driven data processing (Kafka, Spark Structured Streaming, Flink) • Preferred: General knowledge of American football, the NFL, and college football • Preferred: Background in data governance, lineage, and observability tools (Monte Carlo, Great Expectations, Unity Catalog, OpenLineage) • Preferred: Experience designing semantic layers or metric definitions consumed by AI and BI tools • Preferred: Exposure to best practices in machine-learning model management and MLOps
• Competitive Salary and Bonus Plan • Comprehensive health insurance plan • Retirement savings plan (401k) with company match • Remote working environment • A flexible, unlimited time off policy • Generous paid holiday schedule - 13 in total including Monday after the Super Bowl • Annual performance bonus, benefits and/or other applicable incentive compensation plans may be included in the total compensation package
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