Data Engineer

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Description

About the role Design, develop, and maintain ETL/ELT pipelines to extract, transform, and load data from multiple sources into data lakes and data warehouses. Build data transformation logic and develop data models to support analytics and machine learning workflows. Requirements Design, develop, and maintain ETL/ELT pipelines to extract, transform, and load data from multiple sources into data lakes and data warehouses. Build data transformation logic and develop data models to support analytics and machine learning workflows. Collaborate with Product Analysts, Data Scientists, and ML Engineers to ensure data is accurate, accessible, and ready for use. Maintain data quality controls, data catalogs, orchestration, logging, and monitoring processes. Apply test-driven development practices to improve the reliability of data solutions. Contribute to information architecture and follow version control best practices using Git. Use Generative AI tools where relevant and continue developing AI-enabled data engineering practices. Qualifications Strong experience with Databricks and AWS services such as S3, IAM, Redshift, Glue, Lambda, Step Functions, and CloudWatch. Hands-on experience with ETL/ELT development and workflow orchestration. Strong proficiency in Python and SQL. Experience with GitHub/GitLab and CI/CD pipelines, especially GitHub Actions. Familiarity with GenAI-powered development tools such as GitHub Copilot or similar tools is a plus. Good communication skills with

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