Job Opportunities API

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 Mid-Level Data Engineer to add to our team. Quick Position Overview: US Citizenship is required Bachelor's Degree is required minimum of 3-5 years' position related experience is required The Role:   STS is looking for a Mid-Level Data Engineer to join a federal data engineering team. You will work alongside senior engineers building and maintaining ETL pipelines on a cloud-based Enterprise Data Platform (EDP) built on AWS, working 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 willingness to learn, strong attention to detail, and a team-first mindset are prerequisites for this position.     This position is contingent upon contract award.   The Mid-Level Data Engineer at STS will:   Develop new ETL pipelines and data ingestion processes alongside senior engineers using AWS Glue (Spark-based,  PySpark ), MWAA (Airflow), Lambda, and SNS, fully conforming to the agency's Enterprise ETL Standards, ETL Common Library, and PEP 8 Python coding standards   Integrate the agency's ETL Common Library into Glue jobs for standardized orchestration, error handling, metadata recording, and SNS notifications for all success and error job events   Ingest structured and semi-structured datasets (CSV, XML, JSON, Avro, pipe-delimited) into S3 landing, raw, and curated zones using Apache Iceberg tables with Parquet as the default format; enforce transactional loading and prevent duplicate loads per dataset reporting period   Configure static ETL metadata in the centralized PostgreSQL metadata store; ensure dynamic metadata records job status and timestamps for all key execution steps   Monitor assigned production jobs and  participate  in operations support rotations;  identify  and escalate failed jobs and performance issues promptly to  maintain  data availability within contractually required ingestion timelines   Ensure ETL Load Reports are populated in real-time and ETL Gap Reports are updated on a weekly basis covering all gaps from the  inception  of the initial ingest process   Build and  maintain  materialized views and semantic layer objects in Trino and Athena to ensure optimized query performance and consistent business logic   Produce and  maintain  required documentation for each assigned dataset: Business Requirements, ETL Design Documents, Data Models (Mermaid format), Data Dictionaries, Mapping Documents, Deployment Documents, O&M Guides, and ETL Test Plans   Write unit and integration tests achieving the 90%  minimum  code coverage threshold; complete security scans at least once per sprint as part of the Definition of Done   De