Lead Analyst - Data Operations

• Own the incoming request queue and serve as the first point of triage for all L1/L2 tickets raised to the Data Desk
• Accurately categorize every request across the four tracks (Logic, Exports, Ops, and Finance) and route to the appropriate pod lead or analyst without delay
• Monitor SLA performance across the queue in real time; proactively surface blockers to the Head of Data Ops before SLAs are breached
• Maintain and continuously refine the triage playbook, updating categorization rules as request patterns evolve
• Systematically identify repeat requests and flag them for automation; scope, design and ship self-service dashboards and automated data pipelines with Pod Leads
• Coordinate with the Analytics Engineering pod to ensure automated outputs conform to Sun King data quality and governance standards
• Perform 100% of code reviews for entry-level analysts before any output is delivered to a business stakeholder
• Review SQL, LookML, and dashboard logic for correctness, performance, and alignment with the Sun King Data Standard
• Run daily stand-ups for the Data Desk team and conduct regular 1-on-1s with direct reports
• Onboard new Freshers into the Data Desk's processes, tooling, and quality standards as part of the Data Academy rotation curriculum
• Represent the Data Desk in cross-functional ceremonies (sprint reviews, stakeholder check-ins) when the Head of Data Ops is unavailable

Qualifications & Experience:

• Bachelor's or Master's degree in a technical field such as Computer Science, Data Science, Statistics, or a related discipline
• 4-9 years of experience in a data, analytics, or data operations function, with at least 1-2 years in a role with direct responsibility for reviewing, mentoring, or managing junior data analysts
• A track record of translating recurring manual work into automated or self-service solutions

Skills & Competencies:

• Strong hands-on SQL skills
• Working knowledge of LookML or equivalent BI layer logic (Looker, Tableau, Power BI, Metabase)
• Familiarity with AWS-based data environments
• Pride in operational precision and satisfaction in growing junior talent