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# Big Data Engineer

- **Company:** Spectraforce
- **Location:** Reston, VA, United States
- **Experience:** Experienced
- **Contract:** Temporary contract
- **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Data Architecture, Data Centers, Information Engineering, Data Governance, Data Integrity, Extract Transform Load (ETL), Data Systems, Apache Hadoop, Python (Programming Language), SQL Databases, Unstructured Data, Apache Spark, Containerization, Kubernetes, Information Technology, Apache Kafka, Data Pipelines, Docker
- **Published:** August 24, 2026
- **Apply:** http://leoforce.us/Careers/Spectraforce/JobDetails.html?jobid=3b0b198f-ed38-4833-9385-f12d44d3a382&OrgId=1&UserId=2818

## About the Role

* Bachelor's degree in Computer Science, Data Engineering, or related field.
 * 3-5+ years of experience in big data engineering roles.
 * Proficiency with big data cloud platforms (AWS, Azure) and tools such as Hadoop, Spark, Kafka.
 * Strong skills in Python, SQL, and data modeling techniques., * Experience with containerization (Docker/Kubernetes) and CI/CD pipelines.
 * Familiarity with data governance frameworks and enterprise data architecture.
 * Knowledge of engineering and construction workflows is a plus.

## Description

The Big Data Engineer will design, develop, and maintain Client's big data ecosystem to support advanced analytics and data-driven decision-making across engineering, procurement, and construction workflows. This role is pivotal in enabling scalable, secure, and efficient data solutions for projects in semiconductor, electric vehicle, advanced materials, and data center sectors.

Job Dimensions:

 * Supervision Received: Reports to Digital Solutions Lead and works under general direction.
 * Supervision Exercised: May provide technical guidance to junior engineers or analysts.
 * Contacts: Frequent interaction with data scientists, project managers, IT teams, and business stakeholders., * Design and implement big data architectures, including ingestion, processing, and modeling of heterogeneous data sources.
 * Develop and maintain ETL/ELT pipelines for structured and unstructured data.
 * Work closely with data scientists, analysts, and business SMEs to deliver actionable insights.
 * Integrate big data solutions with Client's digital ecosystem and project execution platforms.
 * Ensure data reliability, security, and compliance with client's governance policies.
 * Optimize data workflows for scalability and efficiency.
 * Explore emerging technologies and frameworks to enhance data engineering capabilities.
 * Support automation and advanced analytics initiatives across projects.


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