PFF (Pro Football Focus)
https://pff.comAbout
Pro Football Focus (PFF) is a leading sports analytics and performance data company that focuses on delivering the most detailed football insights available to the industry. They analyze every player on every play across NFL, NCAA and other leagues, producing advanced performance grades, analytics, and tools that are trusted by professional teams, coaches, media, agents, fantasy and betting communities worldwide.
Founded in 2007 and now headquartered in Cincinnati, Ohio, PFF’s data informs front-office decisions, supplements scouting workflows, and powers predictive tools that help clients across football organizations gain a competitive edge.
Tech stack
React.jsCandid answers by the company
PFF provides in-depth football analytics by grading every player on every play, and delivers advanced metrics, statistics, rankings and decision-making tools to teams, media, fantasy players and bettors.
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Jobs at PFF (Pro Football Focus)
Senior Data Engineer
About Pro Football Focus (PFF)
Pro Football Focus (PFF) is a global leader in sports analytics, delivering the most comprehensive football data and insights in the industry. Trusted by all 32 NFL teams and numerous collegiate programs, PFF transforms game film into advanced analytics and decision-support tools that power winning strategies.
With a strong focus on data science, engineering excellence, and innovation, PFF builds scalable data platforms that process massive volumes of structured and unstructured football data — enabling teams, media, and fans to make smarter, data-driven decisions.
Key Responsibilities
- Design and build scalable ETL pipelines for large-scale data transformation and ingestion
- Handle both one-time bulk data migrations and real-time streaming data updates
- Develop and maintain data workflows that ensure reliability, quality, and performance
- Design efficient data storage strategies using relational and columnar databases
- Make architectural decisions on when to use columnar vs relational systems
- Work with and contribute to data lake architectures and data warehousing solutions
- Optimize query performance and data modeling strategies
- Collaborate with backend engineers, data scientists, and product teams
- Contribute to API layers including GraphQL integrations where required
- Ensure best practices around data governance, scalability, and observability
Required Skills & Experience
- 5+ years of relevant experience in Data Engineering
- Strong experience writing and maintaining ETL pipelines
- Hands-on experience with large-scale data transformation and storage
- Solid understanding of:
- Relational databases (e.g., PostgreSQL, MySQL)
- Columnar databases (e.g., Redshift, Snowflake, ClickHouse)
- Knowing when and why to use each
- Strong understanding of Data Lake concepts (S3-based architectures, partitioning, storage layers, metadata management)
- Experience with Data Warehousing concepts (dimensional modeling, star schema, fact/dimension tables)
- Familiarity with GraphQL and data API exposure
- Experience working in AWS ecosystem (S3, Redshift, Glue, Lambda, etc.) preferred
- Strong SQL skills and query optimization knowledge
- Good understanding of performance tuning and scalable system design
Nice to Have
- Experience working with streaming systems (Kafka/Kinesis)
- Experience with infrastructure-as-code
- Exposure to analytics-heavy or sports/media domains
- Experience building or contributing to data lake architecture
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