Geospatial ETL Engineer (TS/SCI) Onsite

Vantor Holdings, Inc.; McLean (VA); On-site; USD 200,000 - 250,000; Full time

Benefits offered by this job

401(k) with company match

Mental health resources

Student loan repayment

Adoption reimbursement

Pet insurance

Job summary

Vantor seeks an experienced ETL Developer to support a geospatial visualization platform. You will design, develop, and optimize NiFi-based ETL pipelines feeding a PostgreSQL database, with emphasis on data quality and real-time troubleshooting.

The role requires on-site work, active TS/SCI clearance with polygraph, and strong Python, SQL, and AWS experience across large geospatial datasets.

Qualifications

• Active TS/SCI clearance with polygraph.
• U.S. Citizenship required.
• Onsite full-time work.
• Strong ETL concepts & best practices.
• Experience with databases for data management.
• SQL proficiency for large datasets.
• API data retrieval experience.
• Proficiency in containerized development and AWS.

Responsibilities

• Design, develop and manage ETL workflows using Apache NiFi.
• Learn and monitor NiFi in AWS and PostgreSQL infrastructure.
• Develop NiFi flows following best practices and implement requested changes.
• Interface with analysts to refine data flow requirements.
• Work with containerized development environment and version control (Git).
• Query and analyze large datasets using SQL and APIs.
• Support data quality, performance, and integrity efforts.

Skills

ETL concepts

SQL queries

Python

Data integration

Containerized dev

AWS

Git

Geospatial data

Education

Bachelor’s degree in CS/Engineering/Geography

Tools

NiFi

PostgreSQL

Airflow

NiFi Registry

Git

Job description

Vantor seeks an experienced ETL Developer to support a geospatial visualization platform. You will design, develop, and optimize NiFi-based ETL pipelines feeding a PostgreSQL database, with emphasis on data quality and real-time troubleshooting.

The role requires on-site work, active TS/SCI clearance with polygraph, and strong Python, SQL, and AWS experience across large geospatial datasets.