Data Engineer designing and implementing cloud-native data ecosystem for sports analytics. Building scalable infrastructure to transform raw data into valuable consent assets.
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
Requirements
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.
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