Secret-Cleared Database Architect for Navy Reserve Data

SimVentions, Inc - Glassdoor 4.6; Norfolk (VA); On-site; USD 60,000 - 80,000; Full time

Benefits offered by this job

ESOP

401(k) matching

Healthcare benefits

Job summary

SimVentions, Inc. is seeking a Database Architect to join our Virginia Beach team on-site. The role requires an ACTIVE Secret Clearance and supports the Navy Reserve data ecosystem with data management, analytics, and modernization.

You will implement industry standards for enterprise pipelines, improve observability, and ensure data is accessible, trustworthy, and interoperable. The position emphasizes on-site presence, collaboration with CNR/CNRF, and delivering scalable data solutions while

Qualifications

• 2+ years with Python, PySpark, GitLab, Databricks and/or Jupyter Notebook, SFG, and Magic.
• 2+ years of JavaScript and SQL development.
• 2+ years with Navy Reserve data systems and Advana/Jupyter.
• At least 6 months managing or modifying Alchemy pipeline code.

Responsibilities

• Support CNR and CNRF mission to advance readiness via data-driven decisions.
• Expand and maintain an authoritative data ecosystem for NR data management.
• Automate data feeds into a consolidated data environment.
• Perform capability gap analysis and propose solutions.
• Develop integration strategies for interoperable data across legacy systems.

Skills

Python/PySpark

JavaScript/SQL

Navy Reserve data

Alchemy pipeline

Education

BS in CS/Engineering/related

Tools

GitLab

Databricks

Jupyter Notebook

Secure File Gateway (SFG)

Magic

Job description

SimVentions, Inc. is seeking a Database Architect to join our Virginia Beach team on-site. The role requires an ACTIVE Secret Clearance and supports the Navy Reserve data ecosystem with data management, analytics, and modernization.

You will implement industry standards for enterprise pipelines, improve observability, and ensure data is accessible, trustworthy, and interoperable. The position emphasizes on-site presence, collaboration with CNR/CNRF, and delivering scalable data solutions while