About the role
Job Family: Data Science Consulting Travel Required: None Clearance Required: Ability to Obtain Public Trust What You Will Do: Guidehouse seeks a Data Engineer to support in building, optimizing, and maintaining data pipelines, cloud-based solutions, and analytics platforms. The ideal candidate will have hands-on experience with modern data engineering tools, cloud services, CI/CD, and version control, and will collaborate with cross-functional teams to deliver high-quality, scalable data solutions. Design, develop, and maintain robust data pipelines and ETL processes for ingesting, transforming, and loading data from diverse sources. Build and optimize data architectures and models to support analytics, reporting, and operational needs. Implement and manage CI/CD pipelines for data engineering workflows using tools such as Jenkins, Maven, and Git. Develop and deploy cloud-based solutions leveraging AWS (S3, Lambda, ECS, SQS), Azure (CosmosDB, Functions), and containerization (Docker, Kubernetes). Collaborate with DBAs and application developers to design and integrate data models, stored procedures, and APIs. Ensure data quality, integrity, and security through rigorous validation, monitoring, and logging (e.g., Splunk, CloudWatch, Kibana). Support data migration, integration, and modernization initiatives, including legacy system upgrades and cloud adoption. Troubleshoot and resolve issues in production environments, ensuring high availability and reliability. Document data flows, processes, and technical solutions for knowledge sharing and compliance. Stay current with emerging technologies and best practices in data engineering, cloud, and DevOps. What You Will Need: U.S. Citizenship/ Green Card is required. A bachelor’s degree is required. Minimum of EIGHT (8) years of experience in data engineering, software development, or related roles. Proficiency in programming languages and technologies, including Java, Python, SQL, and PySpark, as well as API development (RESTful and SOAP). Strong hands-on experience designing and developing data pipelines and ETL processes. Extensive experience with relational and NoSQL databases, such as Oracle, MySQL, PostgreSQL, SQL Server, and MongoDB, including data modeling and stored procedure development. Demonstrated experience with AWS cloud services, including S3, Redshift, Lambda, ECS, and SQS. Experience working with Databricks and large-scale data processing environments. Familiarity with containerization and orchestration technologies, including Docker and Kubernetes. Experience with CI/CD tools and pipelines, such as Jenkins, Maven, Git, GitHub, and Bitbucket. Hands-on experience with monitoring and logging tools, including Splunk, CloudWatch, Kibana, and Elasticsearch. Proven experience operating in Agile development environments. Familiarity with version control and collaboration tools, including Git, Jira, and Confluence. Ability to work independently in a fast-paced environment. Strong analytical and troubleshooting skills. Excellent verbal and written communication skills, with the ability to clearly communicate complex technical concepts to diverse audiences. What Would Be