Build and maintain AWS-based ETL pipelines (Glue/PySpark, MWAA/Airflow, Lambda) to ingest and process terabytes of financial data into an S3 data lake using Iceberg/Parquet. Implement metadata, monitoring, tests (90% coverage), materialized views (Trino/Athena), CloudFormation deployments, documentation, and support agile delivery and operations for federal clients.
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
- Deploy ETL resources using CloudFormation templates through the agency CICD pipeline; submit Change Requests to the Change Control Board within required timelines
- 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
Education and Experience:
Required
- 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
STS is committed to equal employment opportunity and merit-based employment practices. STS provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination, harassment, and retaliation in all employment practices and decisions in accordance with applicable federal, state, and local laws.
Employment decisions at STS are based on individual qualifications, performance, skills, and business needs, without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, sexual orientation, gender identity, genetic information, marital status, or any other status protected by applicable law.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, compensation, training, transfer, discipline, termination, layoff, recall, and leaves of absence.
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