Senior Data Engineer - Simple Technology Solutions

At Simple Technology Solutions , our people are our priority. We know our team members are more than employees—they’re parents, friends, volunteers, artists, and athletes. That’s why we offer flexibility to help them thrive personally and professionally while delivering exceptional solutions to our Federal Government clients.

Our culture is built on collaboration, continuous learning, and excellence. We are mentors and thought leaders who share knowledge and foster growth. Recognized as a “Best Place to Work,” we believe a range of perspectives helps us drive innovation and exceed customer expectations. At STS, taking care of our people isn’t a perk—it’s the standard.

As a HUBZone company, we also offer special incentives for team members living in qualified HUBZones. Check out the HUBZone map HERE to see if you qualify!

Simple Technology Solutions is looking for a Senior Data Engineer to add to our team.

Quick Position Overview:

• US Citizenship is required
• Bachelor's Degree is required
• minimum of 6 years' position related experience is required

The Role:

STS is looking for a Senior Data Engineer to join a federal data engineering team. You will design, build, and maintain well-architected ETL pipelines across the full data lifecycle on a cloud-based Enterprise Data Platform (EDP) built on AWS — from data retrieval through ingestion, transformation, semantic layer delivery, and production operations — fully conforming to enterprise ETL standards and governance requirements. You will work at enterprise scale — processing terabytes of financial data across a large portfolio of automated pipelines — as part of an agile team building systems that support critical government functions. A strong desire for quality, meticulous technical detail, and comfort in a security-conscious federal agile environment are prerequisites for this position.

This position is contingent upon contract award.

The Senior Data Engineer at STS will:

• Design, develop, and maintain data retrieval processes for datasets sourced via APIs, SFTP, HTTPS, FTP, web scraping, and Direct Connect from external providers and internal government filing systems — ensuring data is timely, accurate, and stored in the landing zone within contractually required timelines
• Build and maintain ingestion pipelines using AWS Glue (Spark-based, PySpark), Amazon Managed Workflows for Apache Airflow (MWAA), EMR, Lambda, EventBridge, Step Functions, SQS, and SNS to move datasets from the landing zone through raw and curated zones of the data lake
• Process and ingest large-volume XML filings from the agency's electronic filing system — parsing structured XML into key-value Iceberg tables using Glue PySpark, supporting batch processing, and handling XML schema evolution for minor changes
• Store all curated zone data in Apache Iceberg tables us