Data Engineer

First Principles & Concepts is focused on healthcare transformation and government modernization initiatives. The Data Engineer will support data integration, management, and infrastructure activities, ensuring accurate and accessible healthcare data for reporting and analytics. This role involves collaborating with various teams to maintain data quality and optimize data workflows.

Responsibilities:

• Support development, maintenance, and optimization of data pipelines, data integration processes, and data workflows supporting reporting and analytics activities
• Assist with ingestion, transformation, validation, and organization of healthcare, operational, and program data from multiple sources
• Support development and maintenance of structured datasets, databases, and reporting environments used for analytics and performance monitoring
• Troubleshoot data quality, integration, and processing issues to support accurate and reliable reporting outputs
• Assist with automation of recurring data processing and reporting workflows where appropriate
• Support implementation of data validation, quality assurance, and data governance processes
• Monitor data consistency, completeness, and integrity across reporting and analytics environments
• Maintain technical documentation related to data sources, integration processes, reporting logic, and system workflows
• Support management of data access, version control, and reporting structures aligned with program requirements and organizational standards
• Assist with maintaining secure handling of healthcare and operational data in accordance with applicable requirements and best practices
• Collaborate with analytics and evaluation teams to support preparation of datasets used for dashboards, reporting, and performance measurement activities
• Support development and maintenance of reporting environments and operational data structures
• Assist with identifying opportunities to improve reporting efficiency, data accessibility, and workflow automation
• Support troubleshooting and resolution of reporting and data-related issues impacting program operations
• Collaborate effectively across technical, operational, analytical, and program teams in a fast-paced and highly collaborative environment
• Demonstrate professionalism, accountability, responsiveness, and strong technical problem-solving capabilities
• Support a culture of operational excellence, data quality, and continuous improvement

Requirements:

• Bachelor's degree required in Computer Science, Information Systems, Data Engineering, Data Analytics, Software Engineering, or a related field
• Minimum of 5 years of experience supporting data engineering, database management, data integration, or reporting infrastructure activities
• Strong understanding of data integration, data transformation, database management, and reporting infrastructure concepts
• Experience supporting data pipelines, data processing workflows, and reporting environments
• Proficiency with SQL, relational databases, and data management tools
• Strong analytical and technical problem-solving skills with attention to detail and accuracy
• Ability to manage multiple priorities and technical support activities in fast-paced environments
• Strong communication and collaboration skills with the ability to work effectively across technical and non-technical teams
• Proficiency with Microsoft Office Suite including Excel, Word, Teams, and SharePoint
• Experience supporting healthcare, public sector, Medicaid, or government-funded program data environments
• Experience supporting reporting environments, data pipelines, data transformation processes, or analytics infrastructure
• Experience working with structured and unstructured datasets from multiple operational or healthcare data sources
• Experience with Power BI, Tableau, Azure data tools, cloud-based reporting environments, or similar platforms
• Familiarity with scripting or programming languages such as Python, PowerShell, or similar tools
• Understanding of data quality, data validation, and data governance practices