F

Fanatics

China-based licensed sports merchandise retailer

Manager Data Engineering

Engineering LeadershipPosted on Nov 12
Full-timeRedwood City, CA, USA$200k - $230k

About the Job

Requirements

  • At least 7 years of experience in data engineering or related software engineering roles, including at least 2 years of direct people management, with a proven ability to lead data and BI engineering teams and deliver production data platforms in a fast-moving environment.
  • Strong SQL skills and proficiency in Python; experience with Java or Scala is a plus.
  • Hands-on experience with Apache Iceberg or similar open table formats; Spark, Kafka, Airflow, or equivalent tools; AWS data services such as S3, Glue, EMR, Redshift, Lambda, and Kinesis; and Snowflake or a comparable warehouse or lakehouse platform.
  • Deep understanding of ETL/ELT pipelines, dimensional and event modeling, orchestration, and distributed processing.
  • Experience with enterprise BI platforms such as MicroStrategy, Tableau, or Omni, and with building governed metric definitions or a semantic layer such as dbt or Cube.dev.
  • Ability to turn ambiguous business questions into durable data contracts, consistent metric definitions, and clear roadmaps, with strong prioritization, stakeholder management, and communication skills.
  • Practical experience using AI-assisted engineering tools and validating their outputs, with a working understanding of how data engineering supports analytics, machine learning, and generative AI.
  • Bachelor's or master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Responsibilities

  • Lead a team of Data Engineers and BI Engineers responsible for building and operating scalable, reliable data pipelines, platforms, and analytics products.
  • Own engineering delivery, develop team members, and ensure high-quality, trusted data supports analytics, business operations, and data science.
  • Lead modernization across batch and streaming pipelines, data lakes, a governed semantic layer, and data governance foundations, while championing AI-first development.
  • Partner with Data Science, Product, Engineering, Marketing teams, and Partners to support experimentation, marketing, funnel analysis, and scalable self-serve analytics.
  • Translate business requirements into technical designs, data contracts, consistent metric definitions, milestones, and measurable outcomes.
  • Communicate progress and risk clearly across technical and business stakeholders, making principled tradeoffs.
  • Build, manage, and grow a high-performing, inclusive team of Data Engineers and BI Engineers with clear expectations, ownership, and career development plans.
  • Own the team's data strategy, roadmap, delivery commitments, and operational priorities.
  • Manage team budget, resourcing, and tooling decisions while balancing new capabilities with platform reliability and technical debt.
  • Deliver trusted, well-documented data products that give business partners consistent, governed answers for decision-making.
  • Enable actionable insights and self-service analytics through enterprise BI platforms and AI tools.
  • Optimize platform performance, scalability, and cost to withstand seasonal demand and traffic spikes tied to major sporting events and product launches.
  • Apply data quality, lineage, privacy, and access controls so the data behind fan and customer experiences can be trusted.
  • Champion AI-first development by embedding AI-assisted tools and agentic workflows into how the team designs, builds, tests, and operates data pipelines and BI solutions, with appropriate human review and validation.
  • Build AI tools and data agents that let users get insights from data through natural-language interaction, alongside canned reports and dashboards.
  • Build and maintain a semantic layer using tools such as dbt, Cube, and Snowflake that defines trusted business metrics once for BI tools and AI applications.
  • Evaluate AI-related tooling based on measurable value, reliability, integration effort, and cost.
  • Own delivery of scalable, high-performance data pipelines and architectures on AWS and Snowflake-based cloud data warehousing.
  • Lead batch and streaming ingestion with patterns for incremental processing, change data capture, schema evolution, backfills, and recovery.
  • Use Apache Iceberg in data lakes to support ACID compliance, schema evolution, and versioning for large-scale datasets.
  • Drive data modeling and productization, designing dimensional and event models that become well-documented products for downstream analytics.
  • Apply AI and technology to improve efficiency, quality, and outcomes.
  • Use data and digital tools to inform decisions and enhance performance.
  • Demonstrate curiosity and adaptability in adopting new technologies and ways of working.
  • Contribute to a culture of innovation and continuous improvement.

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

Recently Posted Jobs

Explore more opportunities at Fanatics

See more jobs