Description

Build and maintain scalable data infrastructure and transformation pipelines on AWS.

This role is on-site.

Responsibilities

• Design and build data transformation pipelines using SQL, DBT, and Jinja templating.
• Develop and maintain data architecture standards for Data Integration and Warehousing using DBT and Amazon Redshift.
• Own the full stack of data modeling in DBT to empower analysts and data scientists.
• Optimize SQL queries for performance, scalability, and maintainability across large datasets.
• Build and manage infrastructure as code using AWS CDK and automate deployment workflows with CodePipeline.

Required Skills

• 8+ years of experience in data engineering and analytics on modern data platforms.
• 3+ years of extensive experience with DBT, including building complex models and packages.
• Deep familiarity with dimensional modeling, data warehousing concepts, and enterprise data models.
• Hands-on experience with AWS Services: Lambda, Step Functions, MWAA, Glue, Redshift.
• Proficiency in Python, PySpark, and Jinja templating.
• Experience with AWS CDK, CodeCommit, and CodePipeline for infrastructure automation and CI/CD.
• Understanding of change data capture concepts and SQL performance tuning (partitioning, clustering, materialized views).

Preferred Skills

• Bachelor’s or Master’s degree in a quantitative or technical field such as Statistics, Mathematics, Computer Science, or Information Technology.
• Experience supporting Agile development processes and collaborating with offshore teams.

Key Skills

Education

Any Graduate