Data Engineer
Baltimore, Anne Arundel County, Maryland, 21276, USA
Listed on 2026-03-01
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IT/Tech
Data Engineer, Data Analyst, Data Science Manager, Data Security
Overview
Th e Senior Data Engineer will play a crucial role in advancing the CDC Foundation's mission by designing, building, and maintaining data infrastructure for a public health organization. This role is aligned to the Workforce Acceleration Initiative (WAI). WAI is a federally funded CDC Foundation program with the goal of helping the nation’s public health agencies by providing them with the technology and data experts they need to accelerate their information system improvements.
Working within Prince George’s County Health Department, the Senior Data Engineer will support the development and operation of the enterprise data platform by building and maintaining data pipelines, supporting data ingestion and transformation, and enabling analytics and reporting use cases. This role collaborates closely with IT, data analysts, and program stakeholders to ensure data is reliable, accessible, and aligned with public health business needs.
The Senior Data Engineer serves as a senior technical contributor supporting the modernization of PGCHD’s enterprise data platform. The role focuses on designing and implementing data engineering solutions, supporting data ingestion, transformation, and enabling analytics and reporting capabilities across public health programs.
The Senior Data Engineer will be hired by the CDC Foundation and assigned to the Prince George’s County Health Department. This position is eligible for a fully remote work arrangement for U.S. based candidates.
Responsibilities- Azure Synapse & Medallion Architecture
- Design and implement Azure Synapse Analytics solutions using Spark pools, dedicated and serverless SQL pools
- Implement and operationalize Medallion Architecture (Bronze, Silver, Gold) layers within Azure Data Lake Storage Gen2 (ADLS).
- Develop reusable, parameter-driven data pipelines leveraging Synapse pipelines and Azure Data Factory–style orchestration.
- Data Ingestion, Transformation & Modeling
- Ingest and integrate data from diverse internal and external public health sources (clinical, operational, surveillance, census, and partner data).
- Build Spark-based transformations and SQL-based data models to cleanse, standardize, and enrich data.
- Design and maintain dimensional and analytical data models optimized for reporting, dashboards, and advanced analytics.
- Performance, Reliability & Cost Optimization
- Monitor, troubleshoot, and tune Synapse workloads for performance, scalability, and cost efficiency.
- Identify and resolve data pipeline failures, data quality issues, and processing bottlenecks.
- Implement logging, monitoring, and alerting for production-grade data pipelines.
- Data Governance, Security & Compliance
- Implement data governance, metadata management, and lineage using Microsoft Purview.
- Support compliance with public health data security, privacy, and regulatory requirements (HIPAA, CDC guidance, and county policies).
- Apply role-based access control (RBAC) and data protection best practices across Azure resources.
- Collaboration & Stakeholder Engagement
- Partner with public health program leaders, analysts, epidemiologists, and informatics teams to translate defined business needs into technical solutions
- Ensure data products are analytics-ready and aligned with reporting, performance management, and decision-support needs.
- Communicate technical concepts, progress, and recommendations clearly to both technical and non-technical stakeholders.
- Engineering Standards & Knowledge Transfer
- Apply data engineering best practices including source control, CI/CD, automated testing, documentation, and code reviews.
- Provide technical guidance related to data engineering implementations and best practices
- Support documentation and knowledge sharing to promote sustainability of data solutions
- Stay current on Azure data platform capabilities and data engineering trends relevant to public health use cases
- Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.
- Minimum 5 years of professional experience in data engineering, analytics engineering, or data warehousing roles.
- Hands-on experience with Microsoft Azure data services, particularly…
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