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Open nowPosted 147 days ago

Senior Data Engineer

EXL34 open roles

Where
United States
Work mode
Remote
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Your applicationOpen nowSenior Data EngineerEXL · United States

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. EXL postings stay open a median of 3 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.6%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.0%30 days
This job: posted 147 days ago

EXL median: 3 days open

The posting

Job Description

Overview /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. You will architect and build scalable data infrastructure that transforms raw data into high-value assets, powering analytics across digital products, fan engagement, and marketing domains. Your work will directly contribute to the development of a world-class customer data platform.

Responsibilities

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

Qualifications

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
  • A great teammate and self-starter, strong detail orientation is critical in this role.
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