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Fanatics

China-based licensed sports merchandise retailer

Staff Data Analyst

Data Management +1Updated on Nov 14
Full-timeUnited States$160k - $200kIn-person

About the Job

Requirements

  • At least 5 years of experience in analytics, analytics engineering, business intelligence, or strategic operations.
  • Advanced hands-on SQL skills, including writing, quality-assuring, and optimizing complex queries.
  • Strong dbt experience, including designing model layers, writing tests, and making architectural decisions.
  • Experience designing or owning a cloud data warehouse environment, including schema design, governance, and data quality; Snowflake is preferred.
  • Experience working closely with data or analytics engineering teams to turn raw data into production-ready models.
  • Experience presenting analysis and recommendations to senior leaders and defending methodology under scrutiny.
  • Experience owning complex, cross-functional projects end to end.
  • Experience building dashboards in Sigma, Tableau, or a comparable tool.
  • High attention to detail, including identifying data quality issues before they surface in leadership reporting.
  • Comfort working in fast-paced, ambiguous environments with shifting priorities.

Responsibilities

  • Own the architecture of CX Operations ecosystem data in Snowflake, including schema design, data layers, access patterns, and the operating model that ensures reliability as it scales.
  • Decide how ecosystem Operations data should be structured, owned, and governed, and align with teams such as Data Engineering on those decisions.
  • Consolidate overlapping or one-off datasets into shared, well-governed sources of truth, and set naming and documentation conventions.
  • Define and track data quality standards for Operations ecosystem data.
  • Build alerting on critical metrics as needed so issues are identified before they reach leadership reporting.
  • Turn raw cross-domain tables into clean, tested, reusable dbt models for the team to build on.
  • Own the team's core models and introduce data tests, code review practices, and modeling standards that catch issues before they reach stakeholders.
  • Review teammates' SQL, models, and dashboards for correctness, performance, and readability, and coach analysts on best practices.
  • Replace manual, one-off data pulls with automated, always-on solutions.
  • Lead complex cross-functional analyses from an ambiguous business problem through scoping, analysis, and a decision-ready recommendation, without formal authority over contributors.
  • Diagnose root causes and surface trends, anomalies, and risks proactively.
  • Support scenario analysis and impact sizing for product initiatives, operational changes, and staffing decisions.
  • Set standards for publication-ready dashboards and reporting, with clearly defined key performance indicators and documented assumptions.
  • Present findings, architecture decisions, and impact to Operations and senior leadership, and communicate knowns, unknowns, and recommendations in high-uncertainty situations.
  • Build narratives around data so stakeholders understand what the numbers say and what actions to take.
  • Mentor and support analysts across the team through standards, reviews, and knowledge sharing.
  • Ensure AI agents are built on validated, trusted data foundations, and contribute the data models and evaluation rigor needed before development begins.
  • Track deployed agents' performance against Operations goals.
  • Provide a point of view on where AI can be trusted in analytical workflows and where human judgment should remain involved.

Desired Qualifications

  • Experience supporting AI/ML workflows, agent builds, or automation initiatives.
  • Python or a similar scripting language for data manipulation and automation.
  • Familiarity with operational key performance indicators across customer support, fraud, payments, or workforce management.
  • Experience in gaming, fintech, sports, or another operationally intensive, high-volume environment.
  • A bachelor's degree in Analytics, Computer Science, Statistics, Economics, or a related field.

About the Company

Fanatics

China-based licensed sports merchandise retailer

Fanatics China is a joint venture between Fanatics Inc. and Hillhouse Capital that localizes and scales licensed sports merchandise for China. It designs, manufactures, and markets fan gear for Chinese consumers, operating a multi-channel model that includes building and running e-commerce sites for global leagues and teams, exploring online marketplaces, and developing physical retail concepts. Its product workflow combines technology, data, and on-demand manufacturing to manage the entire supply chain, enabling fast response to demand. The company differentiates itself through a China-focused approach backed by Hillhouse’s network and investments, its end-to-end vertical commerce model, and partnerships with hundreds of sports organizations, which together help it navigate China’s complex retail landscape. The goal is to satisfy a previously underserved Chinese market for licensed sports merchandise by creating localized products and channels that connect fans with official gear.

Company size
10,001+
Company stage
Growth Equity (Venture Capital)
Total funding
$5.2B
Headquarters
Huangpu, China
Founded
1995

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