AWS Data Engineer

REE Medical

4h•$110,000 - $130,000•Remote

About The Position

As the AWS Data Engineer, you will be instrumental in building, optimizing, and maintaining scalable data pipelines and lakehouse architectures on AWS to enable reliable, high-performance data flows for analytics and reporting. Your primary focus will be designing robust data models, implementing lakehouse solutions using AWS services, and ensuring efficient ingestion, transformation, and storage of data from diverse sources. This is an excellent opportunity to shape a modern data ecosystem using cutting-edge AWS technologies. This position reports directly to the Manager of Engineering.

Requirements

3+ Years Experience with AWS data services including S3, AWS Glue, Lake Formation, Amazon Redshift, Athena, and IAM for fine-grained access.
4+ Years Experience in data modeling for data warehouses and lakehouses.
4+ Years Experience building and orchestrating ETL/ELT pipelines using AWS Glue, Lambda, Step Functions.
Proficiency with SQL and Python.
Hands-on experience with infrastructure as code (CloudFormation/CDK/Terraform) and CI/CD for data workloads.
Strong understanding of data governance, security, and compliance in cloud environments.
Excellent communication and interpersonal abilities, facilitating effective collaboration across technical and business teams.
Experience working in a remote environment.
Proficiency in data visualization tools (Tableau/Power BI) and project management software (Jira, Confluence).

Responsibilities

Data Modeling: Design and implement dimensional and normalized data models optimized for analytical workloads in lakehouse environments.
Lakehouse Architecture: Build and manage modern data lakehouse solutions using AWS services including Amazon S3, AWS Glue, Amazon Redshift Spectrum, and Lake Formation for governance, cataloging, and fine-grained access control.
ETL/ELT Pipelines: Develop, monitor, and optimize batch and near-real-time data pipelines using AWS Glue, AWS Lambda, Amazon Kinesis, and Step Functions.
Data Ingestion & Integration: Ingest structured, semi-structured, and unstructured data from APIs, databases, streaming sources, and third-party systems into the lakehouse.
Infrastructure as Code & Automation: Define and manage data infrastructure using AWS CloudFormation, CDK, with CI/CD pipelines.
Support model training and analytics initiatives by preparing datasets, performing analysis with strong attention to detail, and creating visualizations using AWS Quick Suite.
Perform other duties as assigned.