Senior Data Engineer

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Simple Technology Solutions

WebsiteLinkedInAll Job Openings

51 - 200 employees

🏛️ Government

🤖 Artificial Intelligence

Government • Cloud • Artificial Intelligence

Simple Technology Solutions is a HUBZone small business that specializes in IT modernization and digital experience for government operations. They focus on digitalizing government processes using cloud-native technologies and Agile practices to deliver full-stack digital solutions. The company emphasizes security, scalability, and interoperability in its enterprise approach. They work on enhancing cloud environments, migrating legacy IT systems, and promoting DevSecOps practices. Additionally, Simple Technology Solutions develops enterprise data management strategies using machine learning and AI, modernizes applications, and provides cloud contact center services. They primarily serve federal government agencies, particularly in law enforcement and public safety missions.

📋 Description

• design, build, and maintain well-architected ETL pipelines • work at enterprise scale and process terabytes of financial data • ensure data is timely, accurate, and stored within contractually required timelines • build and maintain ingestion pipelines using AWS Glue • process and ingest large-volume XML filings • store curated zone data in Apache Iceberg tables • prevent duplicate data loads across target destinations • integrate the agency's ETL Common Library into Glue jobs • ensure all ETL jobs populate ETL Load Reports in real-time • implement technical data quality standards • develop and maintain the semantic layer • deploy ETL resources using CloudFormation templates • create and maintain documentation suite for each dataset • support operationalization of statistical outputs and derived data products

🎯 Requirements

• US Citizenship is required • Bachelor's Degree is required • minimum of 6 years' position related experience is required • strong expertise in AWS Glue (Spark-based), PySpark, and Python (PEP 8) • direct experience building large-scale ETL pipelines on AWS • experience with Apache Iceberg, Parquet, ORC, and Avro file formats • experience with PostgreSQL, Redshift, and Oracle; familiarity with NoSQL, knowledge bases, and vector stores • experience with Trino, Athena, and Hive • experience parsing and ingesting large-volume XML datasets with schema evolution handling using PySpark • proficiency with CloudFormation, GitHub branching workflows, CI/CD pipelines • demonstrated ability to produce complete ETL documentation

🏖️ Benefits

• flexibility to help them thrive personally and professionally • collaboration, continuous learning, and excellence • special incentives for team members living in qualified HUBZones