Junior Data Engineer (ETL/GIS)

Peraton•,

1d•$51,000 - $82,000•Remote

About The Position

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. The program integrates marine and anadromous species data from NOAA’s National Marine Fisheries Service into the U.S. Fish and Wildlife Service’s existing platform, creating a unified experience for Endangered Species Act-listed species. The role develops and deploys ETL pipelines, executes data ingestion workflows, and supports spatial data validation in a cloud data Lakehouse environment. It is fully remote, with all work required to be performed within the United States.

Requirements

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 and 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 or ingestion 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 in a cloud data lakehouse environment.
Familiarity with geospatial data formats and coordinate reference systems.

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.

Responsibilities

Develop, test, and deploy ETL pipelines using Databricks Delta Live Tables within a cloud data lakehouse staging environment.
Aggregate and normalize data from multiple authoritative source systems, including spatial formats and coordinate reference systems.
Implement source-to-target transformation logic, including field-level mapping rules, data type conversions, and null-handling logic.
Execute prototype data ingestion workflows using representative taxa and evaluate results against completeness, accuracy, consistency, and spatial integrity 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 data quality defects with severity classifications and remediation tracking.
Maintain 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.