Senior Data Engineer: Scalable AWS Data Pipelines

Empower Retirement; Greenwood Village (CO); Hybrid; USD 106,000 - 149,000; Full time

Benefits offered by this job

Health benefits

401(k) with match

Tuition reimbursement

Paid time off

Volunteer time off

BRGs open to all

Job summary

Empower Retirement in Greenwood Village, CO is seeking a Senior Data Engineer to design, build, and maintain scalable data infrastructure on AWS. You will collaborate with cross-functional teams to translate data requirements into robust solutions.

The role emphasizes data governance, performance optimization, mentoring junior engineers, and contributing to architectural decisions. A strong background in ETL, PySpark, Hadoop/Spark, and AWS is required.

Qualifications

• 4 to 6 years of data engineering experience with scalable ingestion frameworks.
• Proficiency in ETL development using Python, PySpark and Big Data tech (Hadoop/Spark).
• Strong SQL knowledge with Postgres/Redshift/MySQL; hands-on AWS (DynamoDB, EMR Serverless, Lambda).
• Deep understanding of data modeling, ETL processes, and data warehousing concepts.

Responsibilities

• Design, develop, maintain, and optimize scalable data and file ingestion frameworks.
• Collaborate with cross-functional teams to translate data requirements into solutions.
• Implement data governance and security best practices.
• Troubleshoot data integrity and performance issues.
• Mentor junior engineers and contribute to architectural decisions.

Skills

ETL development

Python

PySpark

Spark

SQL

AWS

Data modeling

Agile/Scrum

Mentoring

Education

Bachelor's degree in Computer Science or related field

Tools

Python

PySpark

Hadoop

Spark

Postgres

Redshift

MySQL

DynamoDB

EMR Serverless

Lambda

Job description

Empower Retirement in Greenwood Village, CO is seeking a Senior Data Engineer to design, build, and maintain scalable data infrastructure on AWS. You will collaborate with cross-functional teams to translate data requirements into robust solutions.

The role emphasizes data governance, performance optimization, mentoring junior engineers, and contributing to architectural decisions. A strong background in ETL, PySpark, Hadoop/Spark, and AWS is required.