Data Engineer

You’‘ll be hands-on across the full AWS data stack including data lakes, analytical warehousing, and pipeline orchestration with real ownership of what you build and the autonomy to make it better. You will work across IAM, S3, API Gateway, Lambda, Glue, Lake Formation, Redshift, DynamoDB, RDS, Airflow, and Terraform/CloudFormation - with the latitude to bring in new tools where they make sense., * Own enterprise-scale data pipelines and cloud data warehouse solutions from design to deployment. Your work directly shapes how the business runs

• Build cloud-based pipelines using modern orchestration tools that power real analytics workloads across the company
• Architect and optimize a Redshift data warehouse that fuels business intelligence and reporting at scale
• Drive ETL and data lake architecture decisions. Your ideas on cataloging and lake formation will shape the standard, not just follow it
• Design and build APIs and API gateway integrations that connect systems and unlock data access across the org
• Bring medallion architecture and modern data standards to life
• Work shoulder to shoulder with IT and cross-functional teams. This is a lean group where every voice matters and good ideas move fast
• Take part in every phase of the build. Requirements, design, coding, testing, deployment.
• Troubleshoot and support production platforms that the business depends on every day
• Spot what’’s broken or outdated and bring the fix, this team wants people who see a better way and speak up
• Mentor less experienced engineers and help set team priorities, leadership here is earned through knowledge, not just title
• Help shape the data engineering practice as the company scales at a rapid pace. Get in early and leave your fingerprint on how this team grows

• Recent, hands-on experience building and supporting solutions on AWS, including IAM, S3, API Gateway, Glue or similar data integration services, Lake Formation, Redshift, and relational/NoSQL databases (RDS, DynamoDB)
• Strong working knowledge of a modern workflow orchestration tool for scheduling and managing data pipelines (Airflow, Step Functions, or similar)
• Proficiency in Python and PySpark for building scalable data engineering solutions
• Experience developing and integrating APIs, including API gateway configuration
• Solid understanding of relational database concepts and data modeling best practices
• Familiarity with medallion-style or similarly layered data architecture standards
• Stable, progressive career history demonstrating depth of experience in data engineering roles
• Strong analytical skills paired with excellent written and verbal communication
• Comfortable operating independently with minimal supervision, while collaborating effectively across teams