Principal Data Analyst - Dynamic, SQL, Databricks - REMOTE

Principal Data Analyst - Dynamic, SQL, Databricks - REMOTE WORK - 65647One of our clients is looking for a Principal Data Analyst - Dynamic, SQL, Databricks to join their team remotely.Required SkillsDynamic, SQL, DatabricksJob DescriptionWe are seeking a Principal Data Analyst to lead the documentation and analysis of a legacy data solution as part of a strategic migration to a modern data platform. This role will focus on understanding and mapping current data flows, identifying dependencies, and supporting the planning of modularizing the solution into distinct, manageable components. The ideal candidate will bring expertise in Dynamic SQL, data flow documentation, and impact analysis.Job ResponsibilitiesAnalyze and document the current legacy data solution, focusing on how data moves, transforms, and integrates across the systemDevelop and maintain documentation on how Dynamic SQL queries extract, validate, and trace data across the legacy environmentCreate comprehensive data flow diagrams and documentation to support migration and modularization planningIdentify and assess the impact of splitting the solution into multiple components, including technical dependencies and business implicationsCollaborate with data engineers, architects, and business stakeholders to ensure accurate understanding of current-state architectureProvide recommendations for sequencing, risk mitigation, and transition planningSupport the creation of migration playbooks and technical documentation for future-state implementationJob RequirementsAdvanced proficiency in Dynamic SQL and query optimizationProven experience in documenting complex data flows, including transformation logic and system interactionsStrong ability to perform impact analysis on architectural changes, especially in modularization or phased migration contextsExcellent communication and documentation skills, with the ability to translate technical findings for diverse audiencesExperience working independently and collaboratively in fast-paced environments