Data Engineer

Edgesource Corporation•Chantilly, VA

1d•Hybrid

About The Position

We are seeking a highly skilled and experienced data engineer to join our team. The ideal candidate will have experience working with large-scale enterprise level data systems on cloud-based architecture platform, to include at a minimum integration of large data, protection of large data, and migration of large data.

Requirements

Bachelor's degree in Computer Science, Data Science, Engineering or related field
Active TS/SCI clearance
Minimum of 5 years of experience in data engineering with a focus on large-scale enterprise level data systems
Proficient in cloud-based data technologies, such as AWS, Azure, or Google Cloud Platform
Demonstrated expertise in designing and building large scale enterprise-level data systems
Proven ability to integrate data from multiple sources and formats
Strong understanding of data protection and security best practices
Experience with data modeling, ETL processes, and data quality assurance
Excellent problem-solving skills and ability to work independently and as part of a team

Nice To Haves

Experience working in cloud environments (e.g., AWS GovCloud, Azure Government).
Experience implementing data quality checks, monitoring pipelines, and optimizing performance for large-scale datasets.

Responsibilities

Design, develop, and maintain large-scale enterprise-level data systems using cloud-based architectures
Develop data integration solutions for a variety of data sources and formats
Ensure the integration of data from multiple sources, including internal and external systems, APIs, and third-party tools
Develop and implement data protection strategies, including data encryption, access controls, and disaster recovery plans
Manage and execute data migration projects, ensuring data integrity and accuracy during the migration process
Collaborate with cross-functional teams to define and execute data-related projects and initiatives
Perform data profiling, data cleansing, and data transformation tasks to ensure data quality and consistency
Develop and maintain documentation related to data architecture and data flows
Implement best practices for data management, including data modeling and data quality assurance
Continuously improve the efficiency, scalability, and reliability of data systems and processes
Stay up-to-date with industry trends and emerging technologies related to data engineering