Data & Analytics Engineer building scalable data platforms for Ledgebrook, an insurance company. Designing pipelines, governance, and cloud data systems while partnering with technical and insurance teams.
About the role
- Data Engineer building scalable pipelines for SumerSports’ football intelligence platform. Supporting deep learning, video, LLM, analytics, and AI-driven products across sports.
Responsibilities
- Build and operate robust data pipelines for ingestion, cleaning, and transformation using Databricks, Airflow, or Kubernetes
- Develop efficient 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 (RAG, 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 for reliability, versioning, and lineage tracking
- Implement orchestration and monitoring by scheduling jobs, tracking dependencies, and automating failure recovery
- 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 systems
Requirements
- 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 cross-functionally with ML, product, and analytics teams
- Exposure to LLM-powered data tools, including text-to-SQL, RAG, agent/tool interfaces such as MCP, or natural-language analytics
- Previous work with cloud infrastructure such as AWS, GCP, or Azure
- Experience with container orchestration using Docker or Kubernetes
- Preferred: previous experience with sports, telemetry, or sensor data pipelines
- Preferred: familiarity with streaming frameworks and event-driven data processing such as Kafka, Spark Structured Streaming, or Flink
- Preferred: general knowledge of American football, the NFL, and college football
- Preferred: background in data governance, lineage, and observability tools such as Monte Carlo, Great Expectations, Unity Catalog, or OpenLineage
- Preferred: experience designing semantic layers or metric definitions consumed by AI and BI tools
- Preferred: exposure to machine-learning model management and MLOps best practices
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
- Annual performance bonus
- Benefits and/or other applicable incentive compensation plans
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