Full-timeRemote or Utah

Data Engineer II

Design, build, and optimize scalable ETL/ELT pipelines across AWS (Aurora, Redshift, Glue) that keep data flowing reliably to our engineering, analytics, and product teams — powering the AI-assisted insights behind DetailPage's patented content optimization platform.

Overview

DetailPage.com helps Amazon brands grow organic traffic through content optimization and market segment share insights, using a patented (US Patent No. 12,093,340), AI-assisted process to identify high-traffic keywords and rewrite product content for sustainable organic growth. We're looking for a Data Engineer to build and optimize scalable data pipelines, support our ETL/ELT and API processes, and keep data flowing seamlessly across our organization and to our end users — working closely with engineering, analytics, and product.

What you'll do

Design, develop, and maintain scalable data pipelines using a variety of AWS services
Work with relational databases such as Aurora (PostgreSQL), Redshift, and AWS Glue for large-scale data management
Develop and optimize ETL/ELT processes for smooth data integration from multiple sources
Collaborate with cross-functional teams to ensure data accessibility and integrity across platforms
Use Python, SQL, and Pandas for data manipulation, analysis, and workflow automation
Implement unit testing (PyTest) to ensure code reliability
Manage API integrations and development using FastAPI
Assist with infrastructure as code (IaC) using CDK and Terraform
Build CI/CD pipelines in Jenkins

What we're looking for

SQL mastery – expertise in complex SQL queries and database optimization
2-3 years of experience in Data Engineering with AWS and Python
Linux proficiency – comfortable with shell scripting, common CLI tools, and building/testing Linux-based Docker images
Advanced Python – strong hands-on experience, ideally with Data Engineering tools like PySpark, Pandas, and SQLAlchemy
Git proficiency – comfortable with version control, branching, and collaboration
ETL/ELT experience – proven ability to build and optimize extract, transform, and load processes
Unit testing – familiarity with PyTest or similar tools

Nice to haves

AWS experience with Aurora (PostgreSQL or MySQL), Redshift, Fargate, Lambda, SQS, and IAM, plus tools like Boto3 and the AWS CLI
Airflow expertise, particularly AWS Managed Airflow, for scheduling and orchestrating data workflows
API development experience with API Gateway and FastAPI
Infrastructure as Code experience with CDK or Terraform
Familiarity with caching tools like Redis
Basic DevOps knowledge for CI/CD pipelines and dev workflow optimization
Familiarity with DBT

Compensation