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# Data Engineer

- **Company:** Robert Half
- **Location:** Northern Virginia, VA, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Data Analysis, Big Data, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Warehousing, Distributed Computing Environment, Apache Hadoop, Python (Programming Language), Apache Spark, Data Analytics, Apache Kafka, Data Pipelines
- **Published:** August 28, 2026
- **Apply:** https://www.dice.com/job-detail/8c46899e-0897-4ec4-987a-01b307916b9a

## About the Role

At least 5 years of experience in data engineering, data analytics, or a closely related field.
Strong hands-on experience building and maintaining data solutions with Python.
Practical expertise with dbt for data transformation, testing, and modeling.
Experience working with enterprise data warehouse platforms and dimensional or analytical data models.
Proficiency with Apache Spark for distributed data processing.
Familiarity with big data technologies such as Apache Hadoop and event-driven tools such as Apache Kafka.
Solid understanding of ETL principles, data integration patterns, and data quality best practices., All applicants applying for U.S. job openings must be legally authorized to work in the United States. Benefits are available to contract/temporary professionals, including medical, vision, dental, and life and disability insurance. Hired contract/temporary professionals are also eligible to enroll in our company 401(k) plan. Visit roberthalf.gobenefits.net for more information.

## Description

We are looking for an experienced Data Engineer for a full time opportunity in Northern, Virginia. In this role, you will design reliable data solutions that support analytics and business decision-making while helping improve the overall data environment. The ideal candidate brings strong technical depth in modern data engineering practices and enjoys building scalable systems from the ground up.

Responsibilities:

Design, develop, and maintain robust data pipelines that collect, transform, and deliver high-quality data for reporting and analysis.

Create and optimize data models that support business intelligence, analytics, and operational use cases across the organization.

Build and manage ETL workflows using Python and related technologies to ensure efficient movement of data between systems.

Work with large-scale data processing tools such as Apache Spark and Hadoop to handle complex and high-volume datasets.

Integrate streaming and batch data sources using technologies such as Apache Kafka to support timely and reliable data availability.

Collaborate with analysts, engineers, and business stakeholders to translate data needs into scalable engineering solutions.

Improve data warehouse performance, structure, and reliability to support accurate and accessible enterprise data.

Use dbt and other modern data transformation practices to organize, test, and document datasets effectively.


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