Job Description

Objective:

We are seeking a seasoned Data Engineer to join our Sports Analytics & Engineering Practice. This role is pivotal in shaping and implementing our client’s vision for a cutting-edge, cloud-native data ecosystem in its privacy and consent domain. You will architect and build scalable data infrastructure that transforms raw data into high-value assets, powering analytics with consent data across digital products, fan engagement, and marketing domains. Your work will directly contribute to the development of a customer – privacy and consent centric data platform.

Responsibilities:

• Design and build robust, scalable data transformation pipelines using SQL, DBT, and Jinja templating
• Develop and maintain data architecture and standards for Data Integration and Data Warehousing projects using DBT and Amazon Redshift
• Monitor and ensure the smooth operation of data pipelines between OneTrust (OT) application and external data platforms (ESPs, CRMs, etc.).
• Collaborate with cross-functional teams to gather requirements and deliver dimensional data models that serve as a single source of truth
• Assist in the ongoing data integration tasks (e.g., connectors, APIs) between OT and various business systems.
• Own the full stack of data modeling in DBT to empower analysts, data scientists, and BI engineers
• Enhance and maintain the analytics codebase, including DBT models, SQL scripts, and ERD documentation.
• Familiarize regulatory compliance guidelines across different geographical areas (CCPA, GDPR) and integrate them into current and new pipelines for consent collection.
• Ensure data quality, governance alignment, and operational readiness of data pipelines
• Apply software engineering best practices such as version control, CI/CD, and code reviews
• Optimize SQL queries for performance, scalability, and maintainability across large datasets
• Implement best practices for SQL performance tuning, including partitioning, clustering, and materialized views
• Build and manage infrastructure as code using AWS CDK for scalable and repeatable deployments. Integrate and automate deployment workflows using AWS CodeCommit, CodePipeline, and related DevOps tools
• Support Agile development processes and collaborate with offshore teams

Required Qualifications:

• Bachelor’s or Master’s (preferred) degree in a quantitative or technical field such as Statistics, Mathematics, Computer Science, Information Technology, Computer Engineering or equivalent
• 5+ years of experience in data engineering and analytics on modern data platforms
• 3+ years’ extensive experience with DBT or similar data transformation tools, including building complex & maintainable DBT models and developing DBT packages/macros
• Deep familiarity with dimensional modeling/data warehousing concepts and expertise in designing, implementing, operating, and extending enterprise dimensional models
• Understand change data capture concepts
• Experience working with AWS Services (Lambda, Step Functions, MWAA, Glue, Redshift)
• Hands-on experience with AWS CDK, CodeCommit, and CodePipeline for infrastructure automation and CI/CD
• Python proficiency or general knowledge of Jinja templating in Python and/or PySpark
• Agile experience and willingness to work with extended offshore teams and assist with design and code reviews with customer
• Familiarity with OneTrust or similar consent management platforms is a plus.
• A great teammate and self-starter, strong detail orientation is critical in this role.