[Hiring] Mid-Level Data Engineer @Simple Technology Solutions

Role Description

Simple Technology Solutions 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, processing terabytes of financial data across a large portfolio of automated pipelines. 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.
• 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.
• Configure static ETL metadata in the centralized PostgreSQL metadata store.
• Monitor assigned production jobs and participate in operations support rotations; identify and escalate failed jobs and performance issues promptly.
• Ensure ETL Load Reports are populated in real-time and ETL Gap Reports are updated on a weekly basis.
• Build and maintain materialized views and semantic layer objects in Trino and Athena.
• 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.
• Deploy ETL resources using CloudFormation templates through the agency CICD pipeline.
• Support transition of ETL jobs from other agency teams by verifying standards conformance, performing deployments, and validating data loads.
• Support disaster recovery exercises, pre-production deployments, and ad hoc data requests as assigned.
• Participate in 2-week sprint ceremonies, quarterly PI planning, backlog refinement, and agile delivery using JIRA and GitHub.

Qualifications

• Bachelor's degree or higher in Computer Science, Information Systems, Data Engineering, or a related field.
• 3-5 years of experience in data engineering or a closely related technical role.
• Hands-on experience with Python (PEP 8), PySpark, and SQL for ETL pipeline development.
• Experience with AWS services including Glue, S3, MWAA (Airflow), Lambda, SNS, and SQS.
• Familiarity with Apache Iceberg, Parquet, and ORC file formats and S3 data lake zone concepts.
• Experience with PostgreSQL and basic familiarity with Redshift or Oracle.
• Familiarity with Trino or Athena for query and semantic layer development.
• Experience with CloudFormation, GitHub branching workflows, and CI/CD-integrated deployments.
• Ability to produce clear ETL documentation including data models (Mermaid format) and data dictionaries.
• Understanding of ETL metadata concepts including static and dynamic metadata, load reports, and gap reports.
• Experience in agile development environments with sprint-based delivery.
• Experience supporting IV&V and/or User Acceptance Testing (UAT) processes in a federal or technical program environment.
• Experience with automated testing frameworks; ability to write unit and integration tests achieving defined code coverage thresholds.
• Familiarity with FISMA, NIST 800-53, and OWASP ASVS Level 2 is a plus.
• Must be able to work 8am-5pm Eastern Time regardless of home location.
• Active federal public trust suitability determination or ability to obtain one required.

Benefits

• Flexibility to help team members thrive personally and professionally.
• Special incentives for team members living in qualified HUBZones.