Guidehouse
Data Science Consulting
DataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Data Engineer at Guidehouse. Skills: Data pipelines, ETL processes, Cloud-based solutions, AWS, CI/CD, Version control. Building, optimizing, and maintaining data pipelines, cloud-based solutions, and analytics platforms. Design, develop, and maintain robust data pipelines and ETL processes for ingesting, transforming, and loading data from diverse sources”
Industry & Context.
analytical and troubleshooting skills
Ability to Obtain Public Trust clearance, Travel: None
What They're Looking For.
Must Have
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, API development (RESTful and SOAP), 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, 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, analytical and troubleshooting skills, Excellent verbal and written communication skills, with the ability to clearly communicate complex technical concepts to diverse audiences
Nice to Have
Experience supporting federal programs and/or large-scale data modernization projects, Certifications in AWS, or other cloud/data engineering domains, Experience with data visualization tools (e.g. , Kibana, Tableau), Familiarity with security best practices and compliance in federal environments, Experience with microservices, Spring Boot, and integration of AI/ML components, Previous consulting experience
What You'll Do.
and maintaining data pipelines
cloud-based solutions
and analytics platforms
and maintain robust data pipelines and ETL processes for ingesting
and loading data from diverse sources
Build and optimize data architectures and models to support analytics
and operational needs
Implement and manage CI/CD pipelines for data engineering workflows
Develop and deploy cloud-based solutions
Integrate data models
Support data migration
and modernization initiatives
Troubleshoot and resolve issues in production environments
and technical solutions
How You'll Work.
Team & Collaboration
Collaborate with cross-functional teams to deliver high-quality, scalable data solutions; Collaborate with DBAs and application developers to design and integrate data models, stored procedures, and APIs
Communication Scope
Excellent verbal and written communication skills; Ability to clearly communicate complex technical concepts to diverse audiences
Full Job Description
**_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 J
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