Public Health Data Engineer

Guidehouse is a consulting and professional services company supporting public-sector and healthcare clients. The company seeks an early-career Public Health Data Engineer to develop and maintain data pipelines, cloud-based data platforms, and analytics solutions while supporting data integration, quality assurance, troubleshooting, and documentation.

Responsibilities:

• Assist in developing, testing, and maintaining data pipelines and ETL/ELT processes that ingest, transform, and load data from various sources
• Support the implementation and enhancement of data models, databases, and cloud-based data solutions
• Participate in data integration, migration, and modernization initiatives under the guidance of senior engineers
• Develop and maintain scripts, queries, and applications using technologies such as Python, SQL, and PySpark
• Support cloud-based data environments and services in AWS and Azure
• Assist with the implementation of CI/CD processes and software development best practices using Git and related tools
• Monitor data pipelines and systems, identify issues, and support troubleshooting and resolution activities
• Perform data validation and quality assurance activities to help ensure data accuracy, completeness, and reliability
• Collaborate with data engineers, developers, analysts, and other stakeholders to deliver high-quality solutions
• Document technical processes, data flows, and system configurations
• Continuously develop technical skills and stay current with emerging data engineering technologies and best practices

Requirements:

• Must be able to OBTAIN and MAINTAIN a Federal or DHS 'PUBLIC TRUST
• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or a related technical field
• Experience in data engineering, software engineering, data analytics, computer science, or a STEM related technical discipline
• Foundational knowledge of programming languages such as Python, Java, or SQL
• Basic understanding of relational databases and data querying concepts
• Familiarity with cloud platforms such as AWS or Azure through coursework, certifications, internships, or professional experience
• Exposure to data integration, ETL, data warehousing, or analytics concepts
• Internship, academic, research, or project experience involving data engineering, cloud computing, or software development
• Exposure to Databricks, Spark, or large-scale data processing technologies
• Familiarity with version control systems such as Git
• Basic understanding of software development lifecycle and Agile methodologies
• Strong analytical, problem-solving, and troubleshooting skills
• Ability to learn new technologies and work collaboratively in a team environment
• Strong verbal and written communication skills
• Familiarity with AWS services such as S3, Lambda, or Redshift, or Azure services such as Azure Data Factory, Azure Functions, or Cosmos DB
• Experience with data visualization or reporting tools such as Power BI, Tableau, or Kibana
• Exposure to CI/CD tools and DevOps practices
• AWS, Azure, Databricks, or related cloud/data certifications
• Experience supporting healthcare, public sector, or federal clients
• Interest in data architecture, machine learning, artificial intelligence, or advanced analytics
• Previous consulting, client-facing, internship, or cooperative education experience