Data Engineer

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