Senior AWS Data Engineer (Data Lakehouse)

Role highlights (quick): AWS Data Lakehouse S3, Lake Formation, Glue (jobs / crawlers / catalog), Step Functions, Lambda, Python / PySpark, Terraform / CloudFormation, GitLab CI.

Role summary:
Build and operate a cloud-native Data Lakehouse on AWS that stores, governs and serves trusted data for analytics and engineering consumers. You ll design ETL/ELT pipelines, implement governance with Lake Formation/Glue, use serverless compute for event-driven processing, and automate infra and deployment through IaC and GitLab CI/CD.

Must-have skills:

• AWS: Lake Formation, S3, Glue (Crawlers, Catalog, Registry, Jobs), Step Functions, Lambda, DynamoDB, IAM
• Programming: Python, PySpark (production Glue jobs)
• DevOps / CI-CD: GitLab (CI pipelines), logging/monitoring best practices
• IaC / Frameworks: Terraform, CloudFormation, Serverless Framework, Stacker (or equivalent templating)
• Strong understanding of Data Lakehouse patterns, metadata/cataloging, partitioning and performance tuning

Responsibilities:

• Design & deliver robust ETL/ELT pipelines using Glue, PySpark and AWS serverless components
• Implement data governance, fine-grained access control, and metadata management via Lake Formation & Glue Catalog
• Build workflow orchestration with Step Functions and event-driven processing with Lambda
• Implement and maintain CI/CD pipelines in GitLab and manage infra using Terraform/CloudFormation/Serverless
• Collaborate with business analytics, data science, and platform teams to onboard data consumers and define SLAs

Nice-to-have:

• AWS certifications (Solutions Architect / Data Analytics)
• Experience with Databricks / Delta Lake / Unity Catalog
• Prior experience on airline or large enterprise data platforms