Note: The job is a remote job and is open to candidates in USA. EXL is seeking a seasoned Data Engineer to join their Sports Analytics & Engineering Practice. This role is pivotal in shaping and implementing a cloud-native data ecosystem, where you will architect and build scalable data infrastructure that transforms raw data into high-value assets for analytics across various digital products.

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
• Collaborate with cross-functional teams to gather requirements and deliver dimensional data models that serve as a single source of truth
• 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
• 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

Skills

• Bachelor's 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
• A great teammate and self-starter, strong detail orientation is critical in this role
• Master's degree in a quantitative or technical field such as Statistics, Mathematics, Computer Science, Information Technology, Computer Engineering or equivalent

Company Overview

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