Junior Data Engineer (TS/SCI)

Vantor•Herndon, VA

1d•$115,000 - $155,000•Onsite

About The Position

Vantor is seeking a motivated, technically capable Junior Data Engineer to support the development, integration, operation, and maintenance of a large-scale data analytics platform for a U.S. Government customer. As part of a multidisciplinary engineering and analytics team, the engineer will develop and maintain pipelines and processing workflows that ingest, transform, integrate, and prepare structured and unstructured data for analysis. The position contributes to scalable data solutions and data quality and governance initiatives, while helping ensure platform reliability, performance, and security in a mission-focused environment. The role requires an active TS/SCI clearance, U.S. citizenship, and onsite work at least 90% of the time or as needs dictate.

Requirements

U.S. citizenship and an active TS/SCI clearance; willingness to obtain a CI poly.
Bachelor's degree in computer science, information systems, data science, engineering, or a related technical field.
One to four years of relevant experience in data engineering, software development, analytics, database administration, or a related technical field; relevant internships or project experience may be considered.
Demonstrated experience in data engineering, software development, database engineering, or a related technical discipline.
Working proficiency in Python and SQL and/or Elastic, including experience developing scripts, data transformations, and automated data processing workflows.
Experience with relational databases or distributed data processing technologies, and a basic understanding of data modeling, ETL/ELT processes, and data integration.
Willingness to work onsite at least 90% of the time or as needs dictate.

Nice To Haves

Experience with data engineering platforms and tools such as Apache NiFi, Elasticsearch, PostgreSQL, or OpenShift.
Experience with distributed data platforms such as Spark, Hadoop, Kafka, or Hive.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Experience with containers and orchestration using Docker and Kubernetes.
Experience with data workflow tools such as Apache Airflow.
Experience with CI/CD, Git, DevSecOps, or automated testing.
Experience with data governance, metadata, lineage, or security.
Experience in government, defense, intelligence, or other regulated environments.

Responsibilities

Develop, maintain, and troubleshoot data ingestion, transformation, and integration pipelines for large-scale data analytics.
Support integration and processing of structured, semi-structured, and unstructured data from diverse sources using distributed data processing technologies.
Assist with deployment, configuration, monitoring, and optimization of data engineering components in cloud-based, on-premises, or hybrid environments.
Implement data validation, quality assurance, and monitoring processes to support data accuracy, consistency, availability, and processing efficiency.
Collaborate with data scientists, analysts, software engineers, and government stakeholders to translate data requirements into technical solutions.
Document workflows, processes, and technical designs.