Runs the Data Desk's day-to-day operations as both technical authority and people manager, within Global Analytics and Technology, reporting to the Head of 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.
Categorize every request across four tracks (Logic, Exports, Ops, Finance) and route it to the right pod lead or analyst promptly.
Monitor SLA performance in real time and escalate blockers to the Head of Data Ops before SLAs are breached.
Maintain and update the triage playbook as request patterns and ticket types change.
Systematically identify "repeat" requests and flag them for automation.
Work with Pod Leads to build self-service dashboards and automated pipelines that retire recurring requests.
Coordinate with the Analytics Engineering pod so automated outputs meet Sun King's 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, keeping the team aligned on priorities and unblocked on active tickets.
Hold regular 1-on-1s with direct reports and track their progress against growth plans agreed with the Head of Data Ops.
Onboard new Freshers into the Data Desk's processes, tooling, and quality standards as part of the Data Academy rotation.
Represent the Data Desk in cross-functional meetings, such as sprint reviews and stakeholder check-ins, when the Head of Data Ops is unavailable.
Requirements
Bachelor's or Master's degree in a technical field such as Computer Science, Data Science, or Statistics.
4-9 years of experience in data, analytics, or data operations, including 1-2 years directly reviewing, mentoring, or managing junior analysts.
Track record of turning recurring manual work into automated or self-service solutions.
Strong hands-on SQL skills, working knowledge of a BI layer such as LookML, Looker, Tableau, Power BI, or Metabase, and familiarity with AWS-based data environments.
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