Position Summary: Our team is seeking a highly analytical, detail-oriented Senior Coordinator to serve as a foundational member of our Analytics and Data Operations function within Excel Analytics. This individual will sit at the intersection of data quality assurance, data governance, and applied analysis - acting as a critical connective layer between our Engineering team & Analytics Ops who depend on accurate, well-structured data to do their best work. The Senior Coordinator will be responsible for establishing and maintaining data governance practices, enforcing data quality standards, documenting data definitions and lineage across our internal and syndicated data ecosystem, and supporting the broader analytics infrastructure that powers our sponsorship valuation and measurement capabilities. This role will be based in the Excel Chicago office.

This is a role for someone who is operationally minded and technically curious - someone who takes ownership of data integrity, builds process where there is none, and holds a high standard for what “trustworthy data” means in a fast-paced client services environment. Candidates with prior experience in data operations, analytics, consulting, or a data governance-adjacent function are strongly preferred.

Within Excel Sports Management, the Excel Analytics team serves as the center of gravity for all commercial marketing insights and analytics including sponsorship measurement, consumer insights, talent analytics and industry/category analysis.  Excel Analytics is comprised of a vertically-integrated team of specialists supporting brand, property and talent clients, from back-end engineering, through to modeling and analytics and finally to our client-facing consultants who interpret and visualize our results.

 Role & Responsibilities:

• Own the ongoing monitoring of data quality across key internal, syndicated, and third-party vendors/data sources.
• Serve as the primary point of contact for day-to-day operational management between vendors and Excel Analytics.
• Oversee Analytics’ core data assets & maintain a working knowledge of data sources, their structure, lineage, refresh cadence, and known limitations.
• Establish and enforce data quality standards while documenting the logical and physical data models for our core analytics data ecosystem - including entity relationships, field mappings, and schema documentation
• Develop and execute recurring data validation routines and automated quality checks to detect anomalies, missing records, schema drift, and inconsistencies before they reach production reporting.
• Perform root cause analysis on data quality issues; document findings and coordinate with Engineering/DevOps to ensure timely resolution
• Build and maintain a data dictionary and metadata repository - defining field-level definitions, acceptable value ranges, business rules, and data ownership for all key datasets
• Partner with Engineering to support data pipeline design, ETL process documentation, and the integration of new data sources into the analytics environment
• Evaluate and document structural changes to data sources (schema updates, field deprecations, new API versions) and assess their downstream impact on dashboards, models, and reporting outputs
• Assist in the evaluation of new data tools, platforms, and syndicated data vendors - contributing to requirements definition and fit assessments
• Support the Analytics Operations and Partnership Insights teams with ad hoc data requests, query writing, and data extraction across internal databases and syndicated data platforms
• Contribute to the development of internal reporting templates and standardized analytical frameworks to drive consistency and efficiency across client deliverables
• Establish a deep understanding of the sponsorship landscape in sports & entertainment

Education & Experience:

• Bachelor’s degree required, preferably in Business Analytics, Statistics, Mathematics, Information Systems, Computer Science, or a related field
• 2-4 years of experience in a Data Consulting, Data Analyst, Data Architect, Data Quality, or governance-adjacent role
• Prior experience in consulting, agency, or professional services environment strongly preferred.
• Exposure to or interest in sports/sports marketing, entertainment/media, or marketing analytics a plus but not required.

Knowledge, Skills & Abilities:

• Familiarity with data modeling concepts (entity-relationship diagrams, dimensional modeling, schema design) and the ability to read and interpret technical documentation
• Proficiency in SQL; ability to write queries to extract, join, and validate data across relational databases
• Working knowledge of Python or R for data manipulation and automation tasks; comfort with scripting to support validation workflows
• Experience with data quality tools, data cataloging platforms, or metadata management systems
• Strong documentation skills - able to write clear process guides, data dictionaries, and technical specifications for both technical and non-technical audiences
• Detail-oriented with a high degree of accuracy; a natural ownership mentality around data integrity
• Strong communicator - comfortable surfacing issues, presenting findings, and collaborating with stakeholders at multiple levels of the organization
• Proactive self-starter who can manage multiple workstreams, prioritize effectively, and operate with minimal supervision
• Intellectually curious and proactive, recognizing opportunity and implementing procedures to enhance efficiencies across the team
• Uncompromised ethics and integrity, always focused on doing what is right for our clients
• Knowledge of the sports and sponsorship landscapes in the US and globally
• Ability to work both independently, and within a team, and establish effective interdepartmental relationships
• Ability to prioritize and manage workflow in an environment of managing multiple projects simultaneously

The pay range for this position is: $70,000 per year - $80,000 per year. This position is also eligible for benefits and discretionary bonus.  

Ultimately, the salary may vary based upon, but not limited to, relevant experience, time in role, business sector, and geographic location, among other criteria.