Mid-Level Data Engineer

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 

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