Data Engineer

Tria Federal (Tria) is seeking a Data Engineer to support the Department of Veterans Affairs (VA), Office of Integrated Veteran Care (IVC) and Veterans Community Care Program (VCCP). The Data Engineer will provide hands-on technical support to strengthen data automation, integration, validation, and reporting capabilities that enable operations and contract readiness. This role will focus on developing and maintaining automated data pipelines, improving data quality and interoperability, and translating complex process workflows into fully automated technical solutions by designing API-driven workflows and consolidating data from diverse data sources. The ideal candidate is a senior data engineer who will help the clients maximize the value of their data across the full analytics lifecycle, including data querying and wrangling, predictive analytics, and supporting connections to data visualization and business intelligence (BI) tools.

Basic Requirements:

3–6 years of experience in data engineering, analytics engineering, or a related technical role.

Bachelor’s degree in computer science, Information Systems, Data Science, Engineering, or a related field (or equivalent experience).

Experience developing, validating, and deploying data engineering solutions using Python, SQL, Databricks, and modern data lake architectures.

Experience designing API-driven workflow automations and data pipelines.

Strong understanding of statistical modeling, predictive analysis, and machine learning.

Experience with JSON, RESTful services, and API data integrations.

Experience working with relational data models, data validation logic, and schema design.

Strong analytical and problem-solving skills, with attention to data quality and detail.

Ability to communicate technical concepts clearly to non-technical stakeholders.

Experience working in Agile or iterative delivery environments

MS Office (Work, Excel, PowerPoint, Visio, SharePoint, Teams).

Additional Qualifications:

Experience supporting federal health, VA, or CMS data environments.

Experience creating development requirements and generating complex and detailed systems architecture products.

Experience parsing or transforming EDI claims data (e.g., 837, 835, 278).

Experience using ArcGIS or similar GIS tools to perform drive‑time and distance calculations for network, access, or provider‑related analyses.

Experience supporting small teams while delivering high-quality analytics solutions.

Experience supporting data governance, data documentation, or knowledge-transfer efforts.

Relevant Certifications:

Databricks Certified Data Engineer

Microsoft Certified: Azure Solutions Architect Expert

Responsibilities:

Data Automation and Integration

Develop and maintain automated data pipelines using Python, SQL, Databricks, APIs, and modern data lake architectures.

Design API driven workflow automations to translate complex business processes into scalable technical solutions.

Support API integrations to enable provider-level validation, waiver processing, and workflow automation.

Data Quality and Validation

Identify, analyze, and resolve data inconsistencies, schema mismatches, and data quality issues across Dataverse, SharePoint, and external data sources.

Implement standardized provider data mapping, and schema design to ensure accuracy and completeness.

Support compliance with access standards and operational reporting requirements through improved data accuracy and completeness.

Reporting and Analytics

Build analytics ready datasets to support predictive analytics, and proactive monitoring.

Enable BI and visualization capabilities by preparing high quality data for Power BI and other reporting tools.

Use ArcGIS or similar GIS tools to perform drive time and distance calculations for access and provider analytics.

Integrate automation outputs and validation results into reporting frameworks to enhance transparency and decision making.

Documentation and Knowledge Transfer

Document data flows, system configurations, integration logic, and data models to support long-term sustainability.

Develop and maintain technical documentation, including data dictionaries and configuration guides.

Participate in knowledge-transfer sessions to upskill client team members and other contractors on analytics and data engineering best practices.

Collaboration and Support

Work closely with project team members, analysts, product owners, and government stakeholders to support execution goals.

Provide regular status updates and contribute to weekly project summaries and deliverables.

Escalate technical risks and dependencies as appropriate to project leadership.