SCI)

Vantor•Herndon, VA

1d•$116,000 - $169,400•Onsite

About The Position

Vantor is seeking an ETL Engineer / Data Scientist to develop and maintain data pipelines that support mission applications, analytics, and data science workflows. The role builds reliable processes for ingesting, transforming, validating, and delivering data from multiple sources, combining hands-on data engineering with practical data science skills. The engineer works with software, platform, and mission teams to connect systems through APIs, automate batch processing, and deliver data in secure, scalable environments. The position is part of a multidisciplinary software development, platform engineering, data engineering, and systems administration team that supports mission-focused applications. The team builds and operates systems and data capabilities for trusted data in analytics and operational use. It works in agile, cross-functional teams and values automation, experimentation, and iterative delivery. Team members contribute across the development lifecycle, from data integration and pipeline development through deployment and sustainment. The position requires U.S. Person status and an active TS/SCI clearance, as well as willingness and ability to obtain a CI polygraph. The position's base pay in the Washington, DC metropolitan area is listed as $116,000–$154,000–$169,400 annually; ranges elsewhere vary by location. Vantor offers a competitive total rewards package, including a 401(k) with company match, mental health resources, student loan repayment assistance, adoption reimbursement, and pet insurance.

Requirements

Current active TS/SCI security clearance and willingness and ability to obtain a CI polygraph.
Bachelor’s degree in computer science, data science, engineering, information systems, or a related field, or equivalent professional experience.
Strong working knowledge of Python for data processing, automation, or application development.
Experience building or supporting ETL workflows and data pipelines.
Experience with Apache Nifi or a comparable workflow orchestration tool.
Experience writing shell scripts for batch processing or system automation.
Experience integrating systems through APIs and handling data exchanges.
Familiarity with CI/CD pipelines and automated software delivery practices.
Experience working with Kubernetes or containerized workloads.
Working knowledge of Linux system administration.
Experience using Git for version control and team development.
Strong troubleshooting and analytical skills, including investigating pipeline failures and data quality issues.
Strong written and verbal communication skills and ability to work effectively on a multidisciplinary team.
Must be a U.S. Person, defined in the posting as a U.S. citizen, permanent resident, Asylee, or Refugee.

Nice To Haves

Experience with OpenSearch, Grafana, or Prometheus for search, monitoring, logging, or observability.
Familiarity with Jira for agile planning and work tracking.
Experience working with S3 or S3-compatible object storage.
Experience with Ansible for configuration management or automation.
Experience building or operating Docker containers.
Experience supporting data science, analytics, or machine-learning workflows.
Experience working in secure, disconnected, classified, or other restricted environments.
Experience in the Department of Defense or Intelligence Community.

Responsibilities

Design, develop, and maintain ETL workflows to ingest, transform, validate, and deliver data from multiple sources.
Build and support automated data pipelines using Python, Apache Nifi, shell scripts, and related tools.
Integrate systems and services using APIs, including developing and troubleshooting API calls and data exchanges.
Develop batch-processing scripts and workflows for scheduled data movement and transformation.
Apply data science techniques to explore, prepare, and analyze data in support of mission and customer needs.
Collaborate with data scientists, software developers, platform engineers, and stakeholders to define data requirements and deliver usable data products.
Deploy and support data services and workloads in Kubernetes-based environments.
Support CI/CD pipelines and automated testing for data workflows and related software.
Use Git and Bitbucket for source control, code review, and team collaboration.
Perform Linux system administration tasks related to data processing, pipeline operations, and application support.
Monitor pipeline execution, investigate failures, resolve data quality issues, and improve reliability and performance.
Create and maintain technical documentation, workflow definitions, operational procedures, and troubleshooting guidance.
Participate in agile ceremonies, backlog refinement, sprint planning, and technical reviews.
Follow security and data-handling requirements for secure mission environments.