About Goods & Services Goods & Services is a product design and engineering company. We solve mission-critical challenges for some of the world’s largest enterprises, with deep expertise in highly regulated industries—including life sciences and financial services. Our design-led approach allows us to apply cutting-edge capabilities in AI, Data and Hardware Engineering to companies of any size. Headquartered in the United States, we operate regional development centers in Mexico and the United Kingdom. This global footprint—anchored by our nearshore model—enables us to deliver at scale with the speed, efficiency, and cultural alignment our clients expect. About the job Goods & Services is looking for a Senior Data Platform Specialist / Cloud Data Engineer to design, build, and maintain scalable data pipelines and AWS data platform services. This role is focused on our AWS data stack, including AWS Glue, Redshift, Apache Airflow, and Apache Iceberg on S3, rather than general-purpose DevOps or cloud infrastructure ownership. This is a hands-on role where you will work closely with analytics engineers, data scientists, and application developers to deliver reliable, cost-efficient data solutions, business-facing data models, and strong FinOps discipline. What you’ll do: 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. What you’ll need: 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. Nice to have: 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).