Data Engineer

Rividium•Quantico, VA

About The Position

RiVidium Inc. is seeking a Senior Data Engineer to support data-driven decision-making by collecting, transforming, and delivering high-quality data. This role is responsible for designing, building, securing, and optimizing scalable data processing systems with a strong emphasis on performance, reliability, security, and compliance.

Requirements

Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related quantitative field
Equivalent work experience may be considered in lieu of a degree
Minimum of ten (10) years of IT experience, including at least six (6) years in data engineering or related disciplines
Strong experience designing and optimizing data pipelines and architectures
Expertise in ETL/ELT processes, data integration, and data warehousing concepts
Proficiency in SQL and programming languages such as Python, Java, R, or Scala
Experience working with large, complex, and heterogeneous datasets
Strong understanding of data modeling, schema design, and metadata management
Experience with cloud platforms (AWS, Azure, GCP) and hybrid environments
Knowledge of DevOps/DataOps practices, including CI/CD for data pipelines
Familiarity with message queuing, stream processing, and real-time data integration technologies
Strong analytical, problem-solving, and communication skills
Ability to design and optimize scalable, high-performance data systems
Strong collaboration skills across technical and business teams
Expertise in data governance, data quality, and data security practices
Ability to translate business requirements into technical data solutions
Adaptability in working with evolving technologies and complex environments
TS/SCI clearance required at contract start

Nice To Haves

Experience supporting Department of Defense (DoD), Department of Navy (DoN), or law enforcement environments
Familiarity with federal data governance and compliance requirements
Experience with data visualization tools such as Tableau, Power BI, or Qlik
Cloud certifications (AWS, Azure, or GCP)
Experience with NoSQL, Hadoop, or big data ecosystems
Experience collaborating with data science teams to operationalize machine learning models

Responsibilities

Design, build, and maintain scalable data pipelines for structured and unstructured data
Develop, optimize, and manage ETL/ELT processes and data ingestion platforms, including cloud-based solutions
Build and maintain data warehouse environments and support data modeling efforts
Ensure data quality, integrity, security, and compliance across all data systems
Collaborate with data scientists, data architects, and stakeholders to deliver data solutions
Support and operationalize machine learning models and analytics workflows
Develop and maintain APIs for data access and integration
Monitor and troubleshoot data infrastructure to ensure performance and reliability
Implement automation using metadata management and modern data engineering practices
Provide ad hoc data analysis and support self-service data access for stakeholders
Design and maintain reporting and dashboarding infrastructure
Promote best practices in data engineering, governance, and data lifecycle management
Support data tagging, metadata management, and enterprise data governance initiatives
Assist in developing data-related policies, documentation, and system requirements
Research and recommend improvements to modernize data architecture, including cloud adoption