Data Engineer: Enterprise Data Pipelines & Analytics

Federal-Home-Loan-Banks-Office-of-Finance; Reston (VA); On-site; USD 138,000 - 212,000; Full time

Job summary

The Data Engineer at Federal Home Loan Banks Office of Finance will serve as the subject matter expert for data engineering across the organization, leading the lifecycle from raw ingestion to data delivery. You will work with on‑premise and cloud platforms to design, implement, and optimize data pipelines and data products that enable accurate analytics and reporting.

Collaborating with data stakeholders, you will drive data discovery, governance, and quality initiatives, build scalable data

Qualifications

• Bachelor’s degree in a quantitative field and 5–7 years of data engineering experience.
• Experience with ETL/ELT design and data quality controls.

Responsibilities

• Design and implement data ingestion, integration, and transformation solutions across sources.
• Develop data pipelines to cleanse, standardize, validate and enrich data for downstream use.
• Monitor data quality and observability tools to prevent issues before they impact consumers.
• Build dimensional models and semantic layers to support analytics.
• Document data assets, lineage, and ownership in the enterprise data catalog.

Skills

Python

SQL

Bash

Data modeling

ETL/ELT

Communication

Data governance

Observability

Education

Bachelor’s degree in Computer Science or related field

Master’s degree preferred

Tools

Azure Data Factory

Azure Synapse

Databricks

Azure Data Lake Storage

Delta Lake

Spark SQL

Power BI

Job description

The Data Engineer at Federal Home Loan Banks Office of Finance will serve as the subject matter expert for data engineering across the organization, leading the lifecycle from raw ingestion to data delivery. You will work with on‑premise and cloud platforms to design, implement, and optimize data pipelines and data products that enable accurate analytics and reporting.

Collaborating with data stakeholders, you will drive data discovery, governance, and quality initiatives, build scalable data