Senior Data/Systems Analyst

Key Responsibilities: Lead the design, implementation, and management of data integration and data platform solutions with a focus on performance, scalability, and reliability Establish and enforce best practices for data integration, ETL/ELT, automation, monitoring, and data quality Design and maintain cloud and/or on-premise data warehouses, data lakes, and data access APIs Oversee data modeling efforts including dimensional modeling, denormalized structures, and OLAP concepts Drive delivery of data engineering initiatives, including structured and unstructured data pipelines Apply data extraction, transformation, and loading techniques to integrate large datasets from multiple sources Support analytical use cases by enabling data availability, quality controls, and reporting frameworks Provide technical leadership, mentorship, and direction to data engineering teams Provide required technical documentation for all relevant deliverables Disclaimer \"The responsibilities and duties outlined in this job description are intended to describe the general nature and level of work performed by employees within this role. However, they are not exhaustive and may be subject to change or modification at any time to meet the evolving needs of the organization and client.

Required Qualifications: Bachelor’s degree in Computer Science, Information Technology, or related field 8+ years of experience in data engineering, including leading teams and delivering scalable data platforms Strong experience designing and developing ETL/ELT pipelines Hands‑on experience with data modeling, relational databases, and application development Expert-level SQL skills Strong problem-solving, analytical, and troubleshooting abilities Excellent communication and organizational skills with the ability to manage multiple priorities U.S. Citizenship is required by the Federal Client Must have or able to obtain DoD Public Trust Clearance

Preferred Qualifications: 3+ years of AWS data engineering experience (e.g., S3, Redshift, Kafka, and related services) Experience building data pipelines using Spark with Java or Scala Strong Java development experience in enterprise environments Familiarity with DevOps tools such as Git, Artifactory, and CI/CD pipelines Expert understanding of data movement, data exchange formats, and database design concepts