Mid-Level Data Analyst

Kforce has a client that is seeking a Mid-Level Data Analyst in Tempe, AZ. Key Responsibilities:

• Perform detailed data analysis on source system data to identify anomalies, inconsistencies, and data quality issues
• Support data analysis, profiling, and transformation activities across legacy and target systems, including movement between relational, NoSQL, and object storage environments
• Develop and maintain two-way data mappings (source-to-target and target-to-source) to ensure completeness, traceability, and alignment with business requirements
• Maintain a strong understanding of target data models, database structures, and data usage patterns to support accurate transformation and validation
• Contribute to the architecture and management of data lake and data warehouse solutions, ensuring data is structured, performant, and accessible for downstream consumption
• Collaborate with Business Analysts, Technical Architects, and development teams to translate business rules into data mappings and transformation logic
• Identify data quality issues, anomalies, and gaps; Support data cleansing decisions; And ensure alignment with approved data mapping and transformation rules
• Perform and support data validation and reconciliation activities to confirm data accuracy, completeness, and usability across all pipeline and migration processes
• Document data flows, schemas, mappings, and transformation logic to support traceability, auditability, and governance requirements
• Contribute to the continuous improvement of data platform architecture, tooling, and data migration strategies in alignment with organizational standards and best practices
• 3+ years of experience in data analysis, development, or a related role supporting data integration or migration initiatives
• Experience supporting data mapping, transformation, and validation activities within data migration or integration contexts
• Solid understanding of database design principles, including relational modeling, normalization, and denormalization strategies
• Proficiency in SQL, including experience with Azure SQL Database, Azure SQL Managed Instance, or similar relational platforms
• Demonstrated ability to move and transform data across structured, semi-structured, and unstructured formats

• Experience with MS SQL Server, Azure Cosmos DB or other NoSQL database platforms supporting distributed or semi-structured data models
• Knowledge of Kusto Query Language (KQL) and experience with Azure Monitor and/or Azure Data Explorer for data analysis, logging, and performance insights
• Experience designing and working with object storage patterns, including blob- and file-based data architectures
• Experience working with data lakes and/or data warehouse platforms (e.g., Azure Data Lake Storage, Microsoft Fabric, or similar technologies)
• Exposure to data science or advanced analytics concepts, including familiarity with platforms such as Azure Machine Learning, Microsoft Fabric/Foundry, Databricks, or similar tools
• Understanding of data governance practices, including data lineage, cataloging, and metadata management to support traceability and auditability of data assets