Data Engineer

Responsibilities

• Develop new ETL pipelines and data ingestion processes using AWS Glue (PySpark), MWAA (Airflow), Lambda, and SNS
• Integrate ETL Common Library for standardized orchestration and error handling
• Ingest structured and semi-structured datasets into S3 using Apache Iceberg and Parquet
• Configure ETL metadata in PostgreSQL metadata stores
• Monitor production jobs and participate in operations support rotations
• Maintain materialized views and semantic layer objects in Trino and Athena
• Produce technical documentation including data models, dictionaries, and mapping documents
• Write unit and integration tests to achieve minimum 90% code coverage
• Deploy ETL resources using CloudFormation through CI/CD pipelines
• Participate in agile ceremonies including sprint planning and backlog refinement

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field
• 3-5 years of experience in data engineering or a related technical role
• Hands-on experience with Python (PEP 8), PySpark, and SQL
• Experience with AWS services (Glue, S3, MWAA, Lambda, SNS, SQS)
• Familiarity with Apache Iceberg, Parquet, and ORC file formats
• Experience with PostgreSQL and familiarity with Redshift or Oracle
• Experience with CloudFormation, GitHub, and CI/CD workflows
• US Citizenship required
• Ability to work 8am-5pm Eastern Time
• Ability to obtain a federal public trust suitability determination

Preferred Qualifications

• Familiarity with FISMA, NIST 800-53, and OWASP ASVS Level 2
• Experience supporting IV&V or User Acceptance Testing (UAT) in federal environments
• Experience with automated testing frameworks

About the Company

Simple Technology Solutions (STS) provides exceptional solutions to Federal Government clients. Recognized as a "Best Place to Work," STS fosters a culture of collaboration, continuous learning, and excellence.