Senior Data Engineer – Cloud, AWS

🕒 June 3

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Goods & Services

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2013

🤖 Artificial Intelligence

🏢 Enterprise

🤝 B2B

Artificial Intelligence • Enterprise • B2B

Goods & Services is a product design and digital engineering company that helps enterprises design, build, and scale AI-powered products, platforms, and customer experiences. They provide services across Data & Artificial Intelligence, Experience Strategy & Design, and Technology & Engineering (cloud, software, hardware), focusing on modernizing data infrastructure, building digital product ecosystems and global web systems, and delivering enterprise-grade cloud and platform engineering for market-leading B2B clients.

📋 Description

• 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.

🎯 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.

🏖️ Benefits

• Health insurance • Professional development • Flexible work arrangements