Tech Data Analyst
Title: Tech Data AnalystRequired SkillsSAS (Code Analysis & Conversion to Snowflake), Snowflake, SQL, Data Analysis, Data Profiling, Source-to-Target Mapping (MapDocs), Data Validation, Data Reconciliation, Data Lineage, Data Governance, ETL Tools (Talend/Informatica), Reporting & Analytics, Unix/Linux, Python, Power BI/Tableau, Data Warehousing, Agile/ScrumAdditional SkillsetsSnowflake Data WarehouseHive Query DevelopmentSQL & Advanced CTE DevelopmentData Migration & ModernizationData Validation & ReconciliationDatabase Object Creation & ManagementData ModelingMachine Learning Pipeline EnablementSageMaker IntegrationPerformance OptimizationDev/Test/QA Deployment ProcessesData Governance & Quality AssuranceJob DescriptionsData Analysis & TransformationAnalyze complex SAS programs, macros, and datasets to understand business logic, data flows, and transformation rules.Perform SAS code analysis and support migration/conversion to Snowflake.Handle multi-format data ingestion including CSV, JSON, TXT, XML, and Parquet files.Interpret and document upstream-to-downstream data transformations across systems.Analyze source data structures, relationships, and dependencies to support data integration initiatives.Source-to-Target Mapping (MapDocs)Create, maintain, and enhance Source-to-Target Mapping documents (STMs / MapDocs).Define detailed transformation logic, business rules, derivations, and field-level mappings.Document data lineage and mapping between source systems, ETL processes, and Snowflake targets.Ensure traceability between source systems (SAS/upstream) and target platforms (Snowflake).Data Quality & ProfilingPerform data profiling to evaluate completeness, accuracy, consistency, uniqueness, and data distribution patterns.Design and implement Data Quality (DQ) checks to ensure data integrity and reliability.Proactively identify, analyze, and resolve data quality issues and anomalies.Support data quality monitoring and reporting across multiple platforms.Data Validation & ReconciliationExecute end-to-end data validation between source systems and Snowflake.Perform record count, aggregate-level, and attribute-level reconciliations.Validate data across staging, integration, and reporting layers.Support defect analysis, root cause identification, issue remediation, and validation signoff.ETL Analysis & SupportAnalyze ETL workflows developed using Talend and Informatica.Collaborate with ETL developers to understand ingestion and transformation logic.Review ETL design documents and validate implementation against business requirements.Support ETL testing, deployment validation, and production support activities.Snowflake & SQL AnalysisDevelop and execute complex SQL queries for analysis, reconciliation, and validation.Analyze Snowflake schemas, tables, views, and data models.Support Snowflake data validation, performance analysis, and optimization initiatives.Validate source-to-target data movement and transformation accuracy.Reporting & MonitoringDevelop and maintain reports and dashboards for operational and business insights.Support Power BI/Tableau reporting and analytics initiatives.Monitor data pipelines to ensure timely delivery aligned with SLA/OLA commitments.Participate in SLA/OLA definition, approvals, monitoring, and performance tracking.Collaboration & SupportCollaborate with ETL Developers, Data Engineers, Architects, Business Analysts, and Business Stakeholders.Support requirement gathering, data analysis workshops, and impact assessments.Support SIT, UAT, production releases, and post-deployment validation activities.Clarify business requirements and document functional specifications.Validate data accuracy and ensure reporting reliability.Coordinate issue resolution with upstream and downstream teams.Data Governance & LineageMaintain data lineage documentation for audit, compliance, and governance purposes.Ensure transparency of data movement across systems and transformations.Support metadata management and governance standards.Maintain technical and functional documentation for regulatory and operational requirements.Ensure adherence to enterprise data governance policies and best practices.