Senior Data Engineer – Databricks, Security & Governance

Peraton•,

2d•$112,000 - $179,000•Remote

About The Position

Peraton is seeking a Database Engineer SME with expertise in cloud data platforms and federal data governance to lead the database design, security implementation, and production migration for a federal data integration program. This program aims to integrate marine and anadromous species data into an existing FWS platform, creating a single, unified experience for all ESA-listed species. The role involves serving as the database authority, ensuring compliance with federal security and governance standards within a hybrid AWS cloud environment.

Requirements

Bachelors degree and 12 years professional experience or a Masters degree and 10 years professional experience or an Associates degree and 14 years professional experience; or a high school diploma/equivalent and 16 years’ professional experience.
U.S. Citizenship required; must have the ability to obtain and maintain a Public Trust clearance
Extensive years of database engineering experience with expertise in cloud data platforms
Hands-on experience with Databricks, Delta Lake, or equivalent cloud data lakehouse platforms
Proficiency in Python or Scala for ETL pipeline implementation, data quality framework development, and database automation scripts
Knowledge of FIPS 140, NIST SP 800-171/800-172, and federal CUI data governance standards
Experience designing and implementing RBAC and data security controls in federal cloud environments
Experience leading database migrations and production cutover activities on federal programs
Experience with version-controlled code repositories and peer review enforcement
Experience documenting post-deployment monitoring results and production validation outcomes
Strong data modeling, schema design, and metadata management skills

Nice To Haves

Experience with AWS GovCloud or equivalent FedRAMP-authorized cloud environments
AWS Certified Database Specialty or AWS Certified Data Engineer certification
Experience with Apache Spark for large-scale distributed data processing within Databricks environments
Familiarity with federal environmental or geospatial data systems
Databricks Certified Data Engineer or equivalent certification
Experience with ETL pipeline data quality framework design
Active Public Trust Clearance

Responsibilities

Lead the design and implementation of the harmonized data schema for federal species data within a cloud data lakehouse, reconciling structural and semantic differences across multiple source systems
Produce the field-level source-to-target mapping document, documenting transformation logic, data type conversions, null handling, and data lineage
Define and enforce metadata standards across all ingested datasets, ensuring consistency, traceability, and regulatory compliance
Design and implement automated data quality validation frameworks within ETL pipelines
Design and build the Metadata and Authoritative Source Registry, cataloging all data sources, ingestion pathways, update frequencies, and data stewardship contacts
Implement FIPS 140-compliant encryption and enforce NIST SP 800-171/800-172 database security controls and role-based access controls
Ensure Federal CUI Registry and data governance standards are applied to all data stored and processed within the platform
Lead database performance monitoring and optimization within the cloud data platform
Contribute to the Data Model Harmonization Report, providing database-layer schema design decisions, field-level mapping documentation, and metadata standard definitions for government review
Lead the development of the production migration runbook database components and execute database migration tasks during production cutover
Contribute to the Production Deployment Report, documenting database migration outcomes, post-deployment data validation results, and production monitoring findings
Lead the Final Operational Playbooks database documentation