AWS Data Engineer (Glue / Redshift / Python)

ERNEST & ERNEST
Seattle, United States of America
20 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
$ 166K

Job location

Seattle, United States of America

Tech stack

Query Performance
Agile Methodologies
Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Data analysis
Big Data
Cloud Database
Information Engineering
Data Governance
Data Infrastructure
Data Integration
ETL
Data Systems
Identity and Access Management
Information Lifecycle Management
Python
Machine Learning
SQL Databases
Workflow Management Systems
Data Processing
Snowflake
Spark
Spring-boot
PySpark
Data Analytics
Amazon Web Services (AWS)
Data Management
Data Pipelines
ServiceNow
Redshift
Databricks

Job 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

Requirements

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

Benefits & conditions

$72 - $80 an hour - Contract

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