Data Engineer

Guidehouse is a consulting firm specializing in data science solutions, and they are seeking a Data Engineer to enhance their data capabilities. The role involves building and maintaining data pipelines, optimizing cloud solutions, and collaborating with teams to deliver high-quality data solutions.

Responsibilities:

• 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

Requirements:

• 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
• 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