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. Key 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
Minimum Qualifications: - 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
Core Competencies: - 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
Clearance Requirement: - TS/SCI clearance required at contract start
Preferred Qualifications: - 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
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