Goods & Services - Senior Data Engineer & Cloud (AWS)
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Requirements
• 5+ years of experience in data engineering, data platform, or cloud data engineering roles with a strong focus on AWS data services. • Hands-on expertise with AWS Glue (PySpark), Redshift, Athena, S3, Glue Data Catalog, Lake Formation, and IAM. • Production experience with Apache Airflow, including DAG development, scheduling, and multi-environment management. • Experience building data warehouse solutions and business-facing analytics models using dbt, Spark, and SQL. • Strong Python skills for building ETL/ELT pipelines and automation tooling. • Familiarity with lakehouse architectures using Apache Iceberg or Delta Lake on S3. • Familiarity with CI/CD tooling such as Jenkins, GitHub Actions, and CodeBuild. • Basic familiarity with data-adjacent AWS infrastructure services such as Lambda, EventBridge, and SQS. • Experience building REST APIs with FastAPI or Flask, particularly for internal Redshift or data platform services. • AWS Certifications (Solutions Architect, Developer, or equivalent).
Responsibilities
• Design, develop, and maintain scalable data pipelines and ETL/ELT processes across AWS cloud environments. • Manage and optimize data platforms using services such as AWS Glue, Redshift, Athena, S3, Glue Data Catalog, Lake Formation, and IAM. • Implement and orchestrate workflows with Apache Airflow for large-scale data processing and analytics. • Build and optimize data warehouse solutions and business-facing analytical models using dbt, Spark, and SQL. • Collaborate with cross-functional teams to deliver secure, scalable, and highly available data solutions. • Support CI/CD pipelines and deployment automation for data platform workflows, especially with CodeBuild, Jenkins, and GitHub Actions. • Architect and maintain lakehouse storage layers on S3 using Apache Iceberg and/or Delta Lake table formats. • Manage AWS Glue Data Catalog, crawlers, and Lake Formation permissions for data governance and access control.
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