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Data Engineersumersports • New Bremen, Ohio, United States
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Data Engineer

sumersports
  • US
    New Bremen, Ohio, United States
  • US
    New Bremen, Ohio, United States
Postuler Maintenant

À propos

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, Luigior 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.
Nice to Have
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.
Benefits
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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  • New Bremen, Ohio, United States

Compétences linguistiques

  • English
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