Financial Management Data Engineer

Guidehouse•Tysons Corner, VA

14h

About The Position

Guidehouse is seeking a Data Engineer to join its AI & Data Practice and support organizational and mission goals through data collection, transformation, integration, and analysis. The role supports decision-making for financial management and information technology programs within the Department of Homeland Security (DHS) Financial Management portfolio. The position involves developing data acquisition and preprocessing solutions, integrating and standardizing data across financial and operational systems, and using analytics to generate insights. It also includes ensuring data governance and quality standards, defining data quality metrics for data ingested into Databricks, facilitating client meetings, and delivering client services while supporting business development, firm initiatives, and professional development.

Requirements

Bachelor's degree.
Three or more years of data experience.
Experience performing data analytics to address management and operational challenges.
Proficiency with data analytics tools such as SQL, Python, R, and Databricks.
Proficiency in Microsoft Office, especially PowerPoint, Word, and Excel.
Prior experience with statistical analysis, predictive modeling, machine learning, and artificial intelligence.
Ability to obtain and maintain a Federal or DoD Public Trust.

Nice To Haves

Active Public Trust or suitability.
Ability to collaborate and work in a team environment and independently.
Ability to identify and address client needs, build client relationships, prioritize and complete tasks flexibly, and communicate potential conflicts to a supervisor.
Effective communication with varied audiences, including management and external clients, in a professional environment.
Ability to facilitate meetings and present topics to diverse groups of functional and technical staff.
Experience in commercial or public sector consulting firms.
Prior experience supporting federal finance organizations.
Experience with cloud platforms and services, including Microsoft Azure, AWS, or similar environments.
Experience with Microsoft Power Platform (Power BI, Power Apps, Power Automate) and SharePoint.

Responsibilities

Access data sources, establish data connections, and develop data ingestion and integration solutions using APIs, databases, file-based interfaces, and enterprise platforms.
Aggregate, clean, and organize datasets from disparate sources and perform quality assurance.
Design and implement data integration, mapping, and standardization frameworks, including configurable business rules and data crosswalks, to support interoperability, reconciliation, and reporting across financial and operational systems.
Manipulate large datasets, perform data mining, and structure raw data using tools such as SQL, Python, and PySpark to identify patterns and generate insights for decision-making.
Design data modeling processes, create algorithms and predictive models, and perform ad hoc and exploratory data analysis to support data-driven decisions, including applying predictive modeling and machine learning.
Ensure data governance and quality assurance standards are met.
Help define data quality metrics for data ingested into Databricks.
Organize and lead client meetings, including scheduling, preparing and delivering agendas and minutes, providing and archiving documentation, and tracking and following up on action items.
Deliver client services while supporting business development, internal firm initiatives, and ongoing professional development.