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# AWS Data Engineer (Glue / Redshift / Python)

- **Company:** ERNEST & ERNEST
- **Location:** Seattle, WA, United States
- **Experience:** Experienced
- **Salary:** $149,760.0 - $166,400.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Agile Methodology, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Big Data, Cloud Database, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Identity and Access Management, Information Lifecycle Management, Python (Programming Language), Machine Learning, SQL Databases, Workflow Management Systems, Data Processing, Snowflake, Apache Spark, Spring-boot, Pyspark, Data Analytics, AWS Data Analytics, Data Management, Data Pipelines, Servicenow, Amazon Redshift, Databricks
- **Published:** June 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=2bfe418b1f9d88e0

## About the Role

Do you have experience in Spring Boot?, * 5+ years of Data Engineering experience building enterprise-scale data solutions

 * 3+ years of hands-on AWS experience in production environments
 * Strong expertise in Python, SQL, and data modeling
 * Experience with AWS Glue, Redshift, Lambda, S3, Step Functions, and related AWS services
 * Strong understanding of ETL/ELT architecture, data integration patterns, and workflow orchestration
 * Hands-on experience with Apache Spark and PySpark
 * Experience optimizing large datasets for performance, scalability, and cost efficiency
 * Knowledge of data governance, security controls, IAM, encryption, and data lifecycle management

Nice to Have

 * AWS Certified Data Analytics - Specialty or related AWS certifications
 * Experience supporting machine learning and advanced analytics workloads
 * Familiarity with Airflow, Databricks, Snowflake, or modern data platform technologies
 * Experience working in Agile development environments

## Description

We are seeking an experienced AWS Data Engineer to help build and scale modern cloud-based data platforms that power business intelligence, analytics, and machine learning initiatives. This is an excellent opportunity to work on large-scale data processing solutions, optimize data pipelines, and contribute to a growing data ecosystem built on AWS.

You'll work alongside data architects, analysts, and data scientists to design reliable, high-performance data solutions that drive critical business decisions.

What You'll Be Doing

 * Design, develop, and optimize scalable ETL/ELT pipelines using AWS-native services
 * Build and maintain cloud-based data lake and data warehouse solutions supporting analytics and reporting workloads
 * Develop robust data integration frameworks using Python and PySpark
 * Design and optimize Amazon Redshift data models and query performance
 * Implement data quality, monitoring, and observability solutions across the data platform
 * Collaborate with data scientists to operationalize machine learning datasets and feature pipelines
 * Improve data governance, security, and compliance practices across AWS environments
 * Support automation initiatives and drive continuous improvements in data processing performance and reliability
 * Manage software asset, entitlement, and licensing data workflows through ServiceNow integrations


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