Data Engineer

Socket.dev; Arlington (VA); On-site; USD 110,000 - 150,000; Full time

Job summary

CALIBRE is seeking an experienced Data Engineer to develop production-ready data products, analytics, and decision-support applications using Army Vantage and DoW War Data Platform capabilities. The role emphasizes hands-on delivery, integrating authoritative data, and creating scalable pipelines and dashboards for timely, trusted decisions.

You will work with mission owners, data stewards, engineers, analysts, and platform teams to improve data quality, develop reusable analytics, and

Qualifications

• Strong experience delivering data pipelines and analytics.
• Proficiency with Python, SQL and PySpark/Spark for data processing.
• Experience building and maintaining data models and dashboards.

Responsibilities

• Ingest, profile, clean, transform, and integrate data from multiple sources.
• Build scalable data pipelines and reusable analytic data products.
• Develop and maintain Vantage/Foundry data models and dashboards.
• Create visualizations with Power BI, Tableau, or Qlik for executives.
• Implement data-quality checks and lineage documentation.
• Collaborate with stakeholders and follow Agile practices.

Skills

Python

SQL

PySpark/Spark

Data modeling

Tools

Power BI

Tableau

Qlik

Job description

CALIBRE is an employee-owned mission focused solutions and digital transformation company. CALIBRE is seeking an experienced Data Engineer to develop production-ready data products, analytics, and decision-support applications using Army Vantage and Department of War (DoW) War Data Platform (WDP) capabilities. The incumbent will translate mission and business questions into governed data pipelines, analytical models, semantic data structures, dashboards, and workflow applications that enable timely, trusted decisions.

This is a hands-on delivery role. The successful candidate will work with mission owners, data stewards, engineers, analysts, and platform teams to integrate authoritative data; improve data quality; build reusable analytics; and transition solutions into sustained operations.

Key Responsibilities

• Partner with functional stakeholders to define decision problems, success measures, data requirements, and minimum viable analytic products.
• Ingest, profile, clean, transform, and integrate structured and unstructured data from authorized enterprise and legacy sources.
• Build and maintain scalable data pipelines, curated datasets, and reusable analytical data products using Python, SQL, PySpark/Spark, and platform-native capabilities.
• Develop and maintain Vantage/Foundry data models, ontology-aligned objects, transformations, workflows, dashboards, and user-facing applications.
• Design mission-appropriate analytical methods, including forecasting, anomaly detection, optimization, or classification when supported by data quality and operational need.
• Develop clear visualizations, dashboards, and executive-ready readouts using Vantage/Foundry tools and as required, Power BI, Tableau, Qlik, or comparable approved tools.
• Implement data-quality checks, lineage documentation, validation tests, model-performance monitoring, and reproducible analytic workflows.
• Apply platform, data-governance, cybersecurity, access-control, and release requirements; coordinate with data owners and stewards to ensure proper use of authoritative data.
• Use Agile delivery practices: refine requirements, estimate work, demonstrate increments, document solutions, and manage technical debt.
• Train end users and analysts; create concise technical documentation, data dictionaries, user guides, and sustainment handoffs.
• Communicate findings, limitations, assumptions, and recommended actions clearly to both technical teams and senior nontechnical stakeholders.