Data Engineer @ Guidehouse

Job Family:Software Development & Support (Digital)Travel Required:Up to 10%Clearance Required:NoneWhat You Will Do:The Data Engineer will work closely with clients, solutions architects and technical/functional leads across Guidehouse digital teams and market segments to support client projects and provide solutions for growth efforts and capabilities build out.Function as a key data team member to develop data pipelines, transformation rules embedding compliance rules and controls to ensure data quality and regulatory compliance.Extract data from vendor systems, transform into canonical models and upload to tools like Snowflake, ensuring data integrity and consistency across enterprise data platforms.Work collaboratively with data scientists, analytics engineers, business analysts, solution architects, and compliance teams to design, build, test, and deploy data products and pipelines that satisfy functional and regulatory requirements.Analyze data dependencies and structures to optimize data flow and ensure efficient data processing across complex enterprise systems.Support data integration initiatives including API-based data ingestion, real-time data processing, and batch data transformation workflows.What You Will Need:US Citizen, Green Card, Green Card – EAD Bachelor's degree. Additional Four(4) years of experience will be needed in lieu of the degree5+ years of experience in data tools, pipelines, and data transformation techniquesStrong proficiency in programming languages like SQL and Python with demonstrated expertise in data manipulation and analysisExperience with ETL/ELT tools and processes (Snowflake preferred) for large-scale data processing and transformationProven ability to work collaboratively with diverse teams and contribute to complex data engineering projectsUnderstanding financial data, regulations, and compliance requirements with ability to embed compliance controls in data processesTechnical Requirements:Core Programming Skills: Strong SQL knowledge and Python proficiency for data processing and automationDatabase Technologies: Experience with DB2 and Snowflake for data storage, retrieval, and managementData Integration: Experience with data integration techniques and APIs for connecting disparate data sourcesETL/ELT Processing: Hands-on experience with data extraction, transformation, and loading processesData Modeling: Understanding of…

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