Overview / Objective
We are seeking an Analytics Data Engineer to join our Sports Analytics & Engineering Practice. This role is focused on turning ingested data into trusted, high-value analytical assets that power dashboards, insights, and decision-making across digital products, marketing, and fan engagement.
You will own the analytics layer of the data platform, building dimensional models and transformation logic that serve as a single source of truth for analysts, data scientists, and BI teams.
Key Responsibilities
- Design and build scalable data transformation pipelines using SQL, DBT, and Jinja templating
- Develop and maintain dimensional data models optimized for analytics and BI consumption
- Own the analytics data layer in DBT, enabling self-service analytics for business users
- Collaborate with product, analytics, and BI teams to translate business requirements into data models
- Enhance and maintain analytics codebases including DBT models, macros, tests, and documentation
- Implement data quality checks, tests, and governance-aligned transformations
- Optimize SQL for performance using partitioning, clustering, and materialized views
- Ensure semantic consistency and metric definitions across dashboards and reports
- Apply software engineering best practices including version control, CI/CD, and peer code reviews
- Support Agile development and collaborate with offshore teams for delivery and reviews
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field
- 5+ years of experience in analytics-focused data engineering
- 3+ years of deep hands-on experience with DBT, including advanced models, macros, and packages
- Strong expertise in dimensional modeling and data warehousing concepts
- Proficiency in SQL performance tuning and large-scale analytical query optimization
- Experience working with Amazon Redshift and modern cloud data platforms
- Familiarity with Python and/or Jinja templating for analytics engineering
- Experience aligning data models with governance, privacy, and access-control requirements
- Agile experience and comfort working with extended offshore teams
- Strong ownership mindset, attention to detail, and passion for building clean, trusted data products
