Data Engineer - CLEARED

This role focuses on designing secure, scalable enterprise data solutions supporting the modernization and cloud migration of a federal background investigation system.
You will architect modern data platforms using AWS services, data lakes, lakehouse patterns, and Medallion Architecture.
The position combines data modeling, ETL/ELT development, database engineering, and performance optimization across large-scale datasets.
You will build reliable pipelines using AWS Glue, Apache Spark/PySpark, SQL, and Python while enabling operational and analytical data integration.
The role requires close collaboration with application developers, infrastructure teams, architects, business stakeholders, and Agile teams.
You will also contribute to data governance, lineage, quality, security, privacy, and retention practices across the enterprise data environment.
This is a fully remote opportunity for a cleared data engineering professional supporting mission-critical modernization initiatives.

• Active Top Secret clearance required on Day 1, with the ability to complete any applicable adjudication or transfer requirements.
• Security+ certification required on Day 1; candidates without the certification will not be considered.
• U.S. citizenship required due to federal contract requirements.
• 7+ years of experience designing, building, and supporting enterprise data engineering solutions and modern data platforms.
• Strong expertise with relational databases such as PostgreSQL, Oracle, and SQL Server, along with semi-structured and NoSQL sources including DynamoDB, JSON, and APIs.
• Extensive experience developing dimensional data models for analytics and operational reporting.
• Hands-on experience with Amazon Redshift and large-scale analytical data environments.
• Strong hands-on experience building ETL/ELT pipelines with AWS Glue, Apache Spark/PySpark, SQL, and Python.
• Experience implementing Change Data Capture using AWS DMS and integrating operational databases with analytical platforms.
• Strong knowledge of AWS data and integration services, including S3, Glue, Redshift, Lambda, EventBridge, SQS/SNS, IAM, CloudWatch, and Secrets Manager.
• Experience developing metadata-driven ingestion frameworks, data lineage processes, and data quality validation solutions.
• Proficiency in data modeling, schema evolution, data versioning, and master/reference data management.
• Strong understanding of event-driven architectures and application/database synchronization patterns.
• Experience optimizing SQL queries, Spark jobs, partitioning strategies, indexing, and Redshift performance for large-scale datasets.
• Experience working in Agile/Scrum environments and collaborating effectively with application developers, architects, and business stakeholders.
• Excellent written and verbal communication skills.
• AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect certification is a plus.
• Experience with enterprise data lakes, lakehouse architectures, metadata repositories, data catalogs, Qlik, AWS Glue Data Catalog, or real-time and near-real-time data integration is preferred.