Job description

Basic Qualifications: • Bachelor’s degree and 0 years of professional experience, or an Associate’s degree and 2 years of professional experience, or a high school diploma/equivalent and 4 years of professional experience. • U.S. Citizenship required; must have the ability to obtain and maintain a Public Trust clearance; all work must be performed within the United States. • Hands-on experience with Databricks and Delta Live Tables or equivalent cloud ETL frameworks • Experience with data quality validation, source-to-target mapping, and data transformation • Experience with data modeling or schema design documentation • Experience documenting test/ingest results and logging defects with severity classifications • Proficiency in Python or Scala for ETL pipeline development • Proficiency in SQL for querying, validating, and transforming data within the cloud data lakehouse environment • Familiarity with geospatial data formats and coordinate reference systems Preferred Qualifications: • Experience with AWS GovCloud or equivalent FedRAMP-authorized cloud environments • Familiarity with GIS tools such as ArcGIS or QGIS • Experience with federal data governance and metadata standards • Databricks Associate certification or equivalent Peraton is seeking a Junior Data Engineer with ETL development and geospatial data experience to support the data engineering workstream on a federal data migration program. You will develop and deploy ETL pipelines, execute data ingestion workflows, and support spatial data validation activities within a cloud data Lakehouse environment. This is a fully remote position. The Department of the Interior (DOI), U.S. Fish and Wildlife Service (FWS), and NOAA's National Marine Fisheries Service (NMFS) have identified a critical gap in the federal government's ability to conduct comprehensive Endangered Species Act (ESA) research. While FWS operates an authoritative web-based platform for managing data for terrestrial and freshwater species, it does not currently include NMFS marine and anadromous species data forcing agencies to rely on separate, manual processes. This program closes that gap by integrating marine and anadromous species data into the existing FWS platform, creating a single, unified experience for all ESA-listed species. Work Location: Remote Day to Day Responsibilities: • Develop, test, and deploy ETL pipelines using Databricks Delta Live Tables within a cloud data lakehouse staging environment. • Execute range data aggregation and normalization activities, collecting data from multiple authoritative source systems and normalizing spatial formats and coordinate reference systems. • Implement source-to-target transformation logic within ETL pipelines, applying field-level mapping rules, data type conversions, and null-handling logic • Execute prototype data ingestion workflows using representative taxa, evaluating results against completeness, accuracy, consistency, and spatial integrity quality criteria. • Document prototype ingestion results, defects, and remediation actions • Produce the Prototype Ingest Results Report, documenting ingestion outcomes, data quality findings, defect severity classifications, and remediation actions for each representative taxa batch. • Log all data quality defects with severity classifications and remediation tracking • Maintain all ETL pipeline code in a version-controlled repository with mandatory peer review documentation. • Support spatial data validation activities in coordination with GIS Engineers. • Support interoperability testing by providing test datasets, pipeline execution support, and data validation assistance. Peraton is seeking a Junior Data Engineer with ETL development and geospatial data experience to support the data engineering workstream on a federal data migration program. You will develop and deploy ETL pipelines, execute data ingestion workflows, and support spatial data validation activities within a cloud data Lakehouse environment. This is a fully remote position. The Department of the Interior (DOI), U.S. Fish and Wildlife Service (FWS), and NOAA's National Marine Fisheries Service (NMFS) have identified a critical gap in the federal government's ability to conduct comprehensive Endangered Species Act (ESA) research. While FWS operates an authoritative web-based platform for managing data for terrestrial and freshwater species, it does not currently include NMFS marine and anadromous species data forcing agencies to rely on separate, manual processes. This program closes that gap by integrating marine and anadromous species data into the existing FWS platform, creating a single, unified experience for all ESA-listed species . Work Location: Remote Day to Day Responsibilities: • Develop, test, and deploy ETL pipelines using Databricks Delta Live Tables within a cloud data lakehouse staging environment. • Execute range data aggregation and normalization activities, collecting data from multiple authoritative source systems and normalizing spatial formats and coordinate reference systems. • Implement source-to-target transformation logic within ETL pipelines, applying field-level mapping rules, data type conversions, and null-handling logic • Execute prototype data ingestion workflows using representative taxa, evaluating results against completeness, accuracy, consistency, and spatial integrity quality criteria. • Document prototype ingestion results, defects, and remediation actions • Produce the Prototype Ingest Results Report, documenting ingestion outcomes, data quality findings, defect severity classifications, and remediation actions for each representative taxa batch. • Log all data quality defects with severity classifications and remediation tracking • Maintain all ETL pipeline code in a version-controlled repository with mandatory peer review documentation. • Support spatial data validation activities in coordination with GIS Engineers. • Support interoperability testing by providing test datasets, pipeline execution support, and data validation assistance. Basic Qualifications: • Bachelor’s degree and 0 years of professional experience, or an Associate’s degree and 2 years of professional experience, or a high school diploma/equivalent and 4 years of professional experience. • U.S. Citizenship required; must have the ability to obtain and maintain a Public Trust clearance; all work must be performed within the United States. • Hands-on experience with Databricks and Delta Live Tables or equivalent cloud ETL frameworks • Experience with data quality validation, source-to-target mapping, and data transformation • Experience with data modeling or schema design documentation • Experience documenting test/ingest results and logging defects with severity classifications • Proficiency in Python or Scala for ETL pipeline development • Proficiency in SQL for querying, validating, and transforming data within the cloud data lakehouse environment • Familiarity with geospatial data formats and coordinate reference systems Preferred Qualifications: • Experience with AWS GovCloud or equivalent FedRAMP-authorized cloud environments • Familiarity with GIS tools such as ArcGIS or QGIS • Experience with federal data governance and metadata standards • Databricks Associate certification or equivalent

Requirements

Must-haves

Bachelor’s degree and 0 years of professional experience, or an Associate’s degree and 2 years of professional experience, or a high school diploma/equivalent and 4 years of professional experience.
U.S. Citizenship required; must have the ability to obtain and maintain a Public Trust clearance; all work must be performed within the United States.
Hands-on experience with Databricks and Delta Live Tables or equivalent cloud ETL frameworks
Experience with data quality validation, source-to-target mapping, and data transformation
Experience with data modeling or schema design documentation
Experience documenting test/ingest results and logging defects with severity classifications
Proficiency in Python or Scala for ETL pipeline development
Proficiency in SQL for querying, validating, and transforming data within the cloud data lakehouse environment
Familiarity with geospatial data formats and coordinate reference systems
Develop, test, and deploy ETL pipelines using Databricks Delta Live Tables within a cloud data lakehouse staging environment.
Execute range data aggregation and normalization activities, collecting data from multiple authoritative source systems and normalizing spatial formats and coordinate reference systems.
Implement source-to-target transformation logic within ETL pipelines, applying field-level mapping rules, data type conversions, and null-handling logic
Execute prototype data ingestion workflows using representative taxa, evaluating results against completeness, accuracy, consistency, and spatial integrity quality criteria.
Document prototype ingestion results, defects, and remediation actions
Produce the Prototype Ingest Results Report, documenting ingestion outcomes, data quality findings, defect severity classifications, and remediation actions for each representative taxa batch.

Nice-to-haves

Experience with AWS GovCloud or equivalent FedRAMP-authorized cloud environments
Familiarity with GIS tools such as ArcGIS or QGIS
Experience with federal data governance and metadata standards
Databricks Associate certification or equivalent
Work Location: Remote
Experience with AWS GovCloud or equivalent FedRAMP-authorized cloud environments
Familiarity with GIS tools such as ArcGIS or QGIS
Experience with federal data governance and metadata standards
Databricks Associate certification or equivalent

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonsqlaws

Platform: peraton
Effort: medium