Data Engineer

TMV Global Inc; Virginia (MN); On-site; USD 95,000 - 120,000; Full time

Job summary

A technology solutions company in Virginia is seeking an AWS Data Engineer to design, build, and maintain scalable data pipelines and ETL solutions. The ideal candidate will have strong experience with Python/PySpark and AWS services, including Lambda, SNS, SQS, Glue, and Redshift. You will be responsible for building ETL pipelines, orchestrating workflows, and ensuring data quality and monitoring. Collaboration with teams to translate requirements into actionable solutions is essential. This role offers the opportunity to work in a dynamic environment.

Qualifications

• Strong experience with Python and PySpark for large-scale data processing.
• Proven hands-on experience with AWS services: Lambda, SNS, SQS, Glue, Redshift, Step Functions.
• Solid SQL skills and familiarity with data modeling and query optimization.

Responsibilities

• Build and maintain ETL pipelines using Python and PySpark on AWS Glue.
• Orchestrate workflows with AWS Step Functions and serverless components.
• Implement messaging and event-driven patterns using AWS SNS and SQS.

Skills

Python

PySpark

AWS Services

SQL

Version Control (Git)

CI/CD

Tools

AWS Glue

AWS Lambda

AWS SNS

AWS SQS

Amazon Redshift

Job description

Overview

Seeking an AWS Data Engineer to design, build, and maintain scalable data pipelines and ETL solutions using Python/PySpark and AWS managed services to support analytics and data product needs.

Responsibilities

• Build and maintain ETL pipelines using Python and PySpark on AWS Glue and other compute platforms
• Orchestrate workflows with AWS Step Functions and serverless components (Lambda)
• Implement messaging and event-driven patterns using AWS SNS and SQS
• Design and optimize data storage and querying in Amazon Redshift
• Write performant SQL for data transformations, validation, and reporting
• Ensure data quality, monitoring, error handling and operational support for pipelines
• Collaborate with data consumers, engineers, and stakeholders to translate requirements into solutions
• Contribute to CI/CD, infrastructure-as-code, and documentation for reproducible deployments

Required Skills

• Strong experience with Python and PySpark for large-scale data processing
• Proven hands-on experience with AWS services: Lambda, SNS, SQS, Glue, Redshift, Step Functions
• Solid SQL skills and familiarity with data modeling and query optimization
• Experience with ETL best practices, data quality checks, and monitoring/alerting
• Familiarity with version control (Git) and basic DevOps/CI-CD workflows