AWS Data Engineer (Glue / Redshift / Python)

ERNEST & ERNEST

Seattle, WA, United States

3 months ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

3 years minimum

Compensation

$149,760.0 - $166,400.0

Working hours

Regular working hours

Job source

indeed.com

Tech stack

Query Performance Agile Methodology Airflow Amazon Web Services Amazon S3 Data Analysis Big Data Cloud Database Information Engineering Data Governance Data Infrastructure Data Integration

+20 more

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

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