SumerSports LLC
Data Engineer
Remote Data Engineering role with clear candidate location fit.
PostedJul 18, 2026
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
USA
Role overview
Data Engineer
Requirements and responsibilities
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Details
- 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.
- 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, product, and analytics teams.
- Experience with sports, telemetry, or sensor data pipelines.
- Familiarity with streaming frameworks (Kafka, Spark Structured Streaming, Flink).
- General knowledge of American football, the NFL, and college football
- Background in data governance, lineage, and observability tools (Monte Carlo, Great Expectations, Unity Catalog, OpenLineage).
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- 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
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