Basketball Scouting Jobs in Washington (NOW HIRING)

Position Overview:

The Senior Data Engineer is responsible for architecting, building, and maintaining data infrastructure in a greenfield stack. This position will design and architect data infrastructure to handle large datasets with varying data including basketball statistical data from the NBA and other leagues, video data, body pose tracking data, basketball qualitative data (e.g. scouting reports), and health and performance data. These datasets will be used by research analysts and data scientists to perform basketball data analysis, as well as by software developers for web and mobile applications.

Do you have a passion for sports!? Are you a creative problem-solver who enjoys building and optimizing data solutions? We'd love to hear from you!

Responsibilities:

• Architect the data engineering infrastructure to be performant, reliable, and scalable.
• Lead data engineering efforts, including making decisions on technologies, providers, database design, partitioning and indexing strategies, and software patterns.
• Create and maintain data pipelines to ingest, validate, and organize critical data using orchestration tools (e.g. Prefect).
• Optimize pipelines and data storage to handle large datasets.
• Build thorough data validation procedures to ensure data is of the highest quality.
• Implement medallion architectures to organize our data structure and provide data lineage.
• Work with key cross-department team members (front office executives, coaches, scouts, salary cap strategists, medical/performance directors, etc.) to build products, implement feedback, and efficiently fix bugs.
• Maintain knowledge of emerging technologies like generative AI and make decisions on how to use them.
• Other duties as assigned.

Minimum Qualifications:

• 5+ years of professional software development experience.
• Strong proficiency with a variety of transactional (OLTP) and analytical (OLAP) databases.
• Sophisticated knowledge of Python and SQL.
• Experience with data engineering frameworks such as Prefect, DBT, etc.
• Experience with open-source backend frameworks such as Rails, Django, Next.js, etc.
• Diverse set of infrastructure experience with both PaaS and IaaS platforms and the ability to dynamically recommend infrastructure stacks and manage associated budgets.
• Experience with Docker.
• Experience working with large datasets.
• Ability to effectively prioritize tasks and manage time efficiently.
• High integrity; dependable and comfortable with confidential information.
• Ability to work effectively with peers.
• Experience with AWS, GCP, Microsoft Azure, or another cloud service.
• Familiarity with agile development frameworks.
• Flexibility to work evenings, weekends, and holidays as needed.

Pay Range: $150k - $190k USD.

Benefit Eligibility: This role is eligible to participate in health and welfare benefits.