Data Engineer - SumerSports LLC

SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia.

Our data-driven platform empowers teams with insights and tools to make informed decisions within salary cap constraints. The platform also serves the NCAA, offering insights around the transfer portal and more.

What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football.

As a Data Engineer , you’ll design, build, and maintain the data pipelines that power our deep learning and LLM systems. You’ll work across ingestion, transformation, and orchestration layers — from real-time feeds to analytics-ready datasets.

Your mission is to make data reliable, discoverable, and scalable for use by model training, analytics, and AI-driven products across multiple sports. You’ll collaborate closely with our MLOps , LLMOps , and Sports Data teams to ensure seamless integration between data and AI.

Responsibilities:

• Build and operate robust data pipelines for ingestion, cleaning, and transformation using Databricks, Airflow, or Dagster.
• Develop efficient ETL/ELT workflows in Python and SQL to support both batch and streaming workloads.
• Collaborate with ML and AI teams to deliver high-quality datasets for training, evaluation, and production features.
• Model and maintain structured data assets (Delta, Parquet, Iceberg) for reliability, versioning, and lineage tracking.
• Implement orchestration and monitoring — schedule jobs, track dependencies, and automate recovery from failures.
• Ensure data quality and compliance through validation frameworks, schema enforcement, and audit logging.
• Contribute to data platform evolution — evaluate tools, standardize best practices, and improve developer experience.
• Support performance and cost optimization across compute, storage, and orchestration systems.

Qualifications:

• 3–6 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 (Delta, Parquet, Iceberg).
• Familiarity with CI/CD, GitHub Actions, and data pipeline testing frameworks.
• Comfort working in a cross-functional environment with ML, pr