Data Engineer

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Reston, VA, US

5 days ago Requisition

FEDERAL HOME LOAN BANKS OFFICE OF FINANCE

POSITION:
Data Engineer DATE:
August 202 6

The Data Engineer will serve as the Office of Finance’s subject matter expert on a multitude of data engineering methods, data integration and data management technologies. This is a highly technical role responsible for leading the data engineering lifecycle across the organization’s data planes — from raw data ingestion through data cleansing, data standardization, data transformation, data modeling, and data delivery.

The scope of the role spans data integration with on-premises source systems through cloud-based data processing, data storing, and works in tandem with other teams who support data serving and data delivery layers.

The Data Engineer works collaboratively across internal data stakeholders and data consumers to identify, prove and implement opportunities to improve data discovery, data collection, data transformation, data standardization, data storage, and data quality. The Data Engineer assists data stakeholders in maintaining an enterprise view of the organization’s data assets, and works with Product Owners/Leaders to consider opportunities to enhance both the organization and the FHLBanks System at large via compelling data products.

We’re proud of the way our teammates have a positive impact on everything we do. Our employees are committed to and exemplify our Core Values:

• Integrity through accountability, consistency,transparency and trust
• Agility through adaptability, continuous improvement,expertise, and flexibility
• Partnership through collaboration, communication, leadership, and teamwork
• Inclusivity through diversity, relationships, respect, and support

• Design and implement data ingestion, integration, and transformation solutions thatconsolidateenterprise data from multiple sources.
• Develop and implement data pipelines to cleanse, standardize,validateand enrich data to ensure data accuracy, consistency, and fitness for downstream use.
• Apply data profiling and statistical analysis techniques to characterize data distributions,identifyanomalies, detect structural problems, and support overall data quality.
• Implement and automate data quality controls andmonitoringtoidentify, prevent, and remediate data issues throughout the data lifecycle.
• Build dimensional models, fact tables, and semantic layers that support downstream analytics and reusability of business data.
• Assist data stakeholders in documenting data assets including lineage, data dictionaries, and ownership through the enterprise data catalog.
• Monitor ETL/ELT data pipeline health and data quality metrics through observability and quality tools, taking proactive steps to address data quality issues before theyimpactdownstream consumers.
• Participate in on-call rotation as needed for support of data products and pipelines.
• Assist with other job duties as assigned.

• Bachelor’s degree in Computer Science , Statistics, Mathematics, Finance, Financial Engineering, Quantitative Finance, Information Science, Data Engineering, or a related quantitative field. Master’s degree or above preferred. A combination of advanced education and directly related experience may be combined to demonstrated subject matter expertise , provided education is a graduate or terminal degree.
• Subject matterexpertisein the following areas:
• At least 5-7 years of data engineering experience withdemonstratedownership of Production data pipelines.
• At least 5-7 yearsdemonstratedexperience in applied exploratory data analysis, descriptive statistical analysis, and inferential statistical analysis in the development and delivery of enterprise data products and data visualizations.
• At least 3-5 years of hands‑on experience with ETL/ELT including job design, dataflow optimization, and integration.
• At least 3-5 years of experience with industry leading analytical data platforms, (e.g., Azure Data Factory, Synapse,…