Analytics Engineer

Salary

Salary Range: $100,000 - $115,000

This position is part of the Data Strategy & Analytics (“DSA”) group, responsible for delivering platforms and products to key stakeholders not represented by positions within the centralized Data, Strategy & Analytics function and will be the advocate for their future needs in the areas of data, technology , and insights. The Analytics Engineer will be responsible for partnering with League Finance to evolve enterprise reporting that drives key decisions and outcomes tied to the team ticketing business. This role will regularly work with leadership across strategic, legal, and technical verticals to align on ou organization’s top financial priorities.

Major Responsibilities

Take technical ownership of key data submission portals, understanding how specific data inputs lead to business outcomes and decisions.
Maintain existing databases that house upstream summarized information from submission portals, including processes that clean and combine data.
Build new data processes to improve the semantic layer for reporting that goes to league and team executives.
Work with Team Marketing & Business Operations (“TMBO”) account managers on various analyses to support decision-making in the ticketing space and other business lines.
Enhance the current report generation processes within DSA through the lens of automation and conversion to different, more useful development environments (e.g., R, Python, DBT).
Streamline existing data collection processes at the league office from teams and create solutions to gather the required information and drive efficiencies.

Required Education/Experience

Bachelor’s degree in quantitative field, with sports focus preferred
2+ years of experience in analytics engineering, data science and/or business intelligence role

Required Skills/Knowledge

Experience with: coding in R or Python, with a background in SQL; BI tools, preferably Tableau or Power BI; Snowflake, Azure, or similar cloud data infrastructures
Developing methods to streamline processes and data flow through automation
Understanding existing data structures, including collection and standardization processes, and ability to help shape future processes going forward with an eye toward business needs
Ability to consult with business analysts and operators to understand their data needs, develop systems to access the data and convert the outputs into various formats for analysis
Comfort with ambiguity in data and experience in working with partners to optimize third-party data streams

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