Join a hybrid team building enterprise data pipelines and AWS cloud data warehouse solutions for production analytics and reporting.

Own enterprise-scale data pipelines and cloud data warehouse solutions from design through deployment
Build AWS-based pipelines using modern orchestration tools to support real analytics workloads across the company
Architect and optimize an Amazon Redshift data warehouse for business intelligence and reporting at scale
Lead decisions for ETL and data lake architecture, including cataloging and lake formation standards
Design and implement APIs and API gateway integrations to connect systems and enable data access across the organization
Implement medallion architecture and modern data standards
Collaborate closely with IT and cross-functional teams in a lean environment where ideas and iteration move quickly
Participate across the full build lifecycle: requirements, design, coding, testing, and deployment
Troubleshoot and support production platforms used day to day by the business
Identify broken or outdated components and drive fixes
Mentor less experienced engineers and help set team priorities through demonstrated knowledge
Contribute to how the data engineering practice evolves as the company scales rapidly

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 and NoSQL databases (RDS, DynamoDB)
Strong knowledge of a modern workflow orchestration tool for pipeline scheduling and management (Airflow, Step Functions, or similar)
Proficiency in Python and PySpark for scalable data engineering work
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 showing depth in data engineering roles
Strong analytical skills plus excellent written and verbal communication
Ability to operate independently with minimal supervision while collaborating effectively across teams

AWS, IAM, S3, API Gateway, Lambda, Glue, Lake Formation, Redshift, DynamoDB, RDS
Airflow, Terraform, CloudFormation
Python, PySpark
API, Step Functions

Senior Data Engineer

Job Description