sai ravi kumar

<p>Developed and maintained Azure Databricks data pipelines for ingestion, transformation, validation, and processing of BMS and EPMS application data.</p><p> Created Databricks notebooks using PySpark and SQL to process structured and semi-structured data from CSV, Excel, and relational database sources.</p><p> Developed data workflows to ingest incoming CSV and Excel files into staging/raw Delta tables in Databricks.</p><p> Implemented Bronze, Silver, and Gold data processing layers to organize raw, cleansed, transformed, and business-ready datasets.</p><p> Developed PySpark transformations for data cleansing, filtering, joins, aggregations, deduplication, and business-rule implementation.</p><p> Created and maintained Delta Lake tables for staging, dimensional, and transactional data.</p><p> Developed SQL and PySpark logic to populate dimension tables and fact tables following data warehouse principles.</p><p> Created reusable transformation logic for loading master/reference data into dimension tables and transaction-level information into fact tables.</p><p> Developed complex SQL queries, CTEs, subqueries, joins, window functions, aggregations, and conditional logic for data extraction and validation.</p><p> Performed data quality checks and source-to-target validation to ensure completeness and accuracy of processed data.</p><p> Developed data extraction processes to generate CSV files and distribute processed datasets to required downstream locations.</p><p> Implemented incremental data processing logic to efficiently process new and modified records.</p><p> Used Delta Lake MERGE operations for handling inserts and updates in curated datasets.</p><p> Developed Power BI dashboards and reports using curated Databricks datasets to provide operational and management-level insights.</p><p> Created Power BI data models using appropriate relationships, calculated columns, measures, filters, and slicers.</p><p> Developed DAX measures and KPIs for analyzing BMS/EPMS operational data and supporting business reporting requirements.</p><p> Implemented interactive Power BI reports with drill-down, filtering, search, and export capabilities.</p><p> Worked with stakeholders and business teams to understand reporting requirements and translate them into Databricks data pipelines and Power BI dashboards.</p><p></p><p> Participated in release management, UAT, production deployment, troubleshooting, and post-production support activities.</p><p> Prepared technical documentation for data workflows, deployment activities, production issues, and release procedures.</p><p> Coordinated with application, infrastructure, database, and business teams to analyze issues and implement efficient solutions.</p>

<p>Developed scalable Azure Databricks and PySpark ETL/ELT pipelines for sanctions-screening data processing.</p><p> Analyzed source-to-target mappings and existing ETL processes to implement business and transformation rules.</p><p> Consolidated Payee, Assured, Claimant, Broker, and Vendor data from multiple heterogeneous source systems into a unified sanctions-screening dataset.</p><p> Developed Databricks notebooks using PySpark and SQL for data extraction, cleansing, transformation, validation, and loading.</p><p> Implemented Delta Lake-based curated tables and incremental data processing using MERGE operations.</p><p> Developed de-duplication and entity matching logic using Entity Name, Entity Type, Address, and other critical attributes.</p><p> Created unique Hash Keys/Business Keys to identify entities and establish links between consolidated records and source-system records.</p><p> Implemented business rules for Activation and Deactivation feeds based on entity status and effective dates.</p><p> Developed data-quality checks for missing mandatory attributes, addresses, invalid records, and failed business rules.</p><p> Performed source-to-target reconciliation and data validation across raw, transformed, and consolidated datasets.</p><p> Supported REST API integration by preparing entity information for Compliance Link and capturing API success/failure responses.</p><p> Developed Power BI HitList reports enabling compliance users to search entities and view linked records across source systems.</p><p> Created Power BI data models, DAX measures, calculated columns, relationships, slicers, filters, and interactive dashboards.</p><p> Used Bitbucket and Jenkins for version control, CI/CD, and deployment of Databricks notebooks and related components.</p><p> Participated in UAT, production deployment, troubleshooting, reconciliation, defect resolution, and hypercare support.</p>

<p>Analyzed business requirements and existing SAP reports and data structures to understand reporting requirements and identify the required source data.</p><p> Worked on the migration of reporting data from SAP systems to SQL Server and supported the development of the enterprise reporting data warehouse.</p><p> Designed and implemented Star Schema data models consisting of fact and dimension tables to support analytical reporting.</p><p> Developed SQL queries, views, stored procedures, and data extraction logic required for reporting and data validation.</p><p> Worked with fact and dimension tables and established appropriate relationships to support Power BI semantic models.</p><p> Developed Power BI dashboards and reports for business users to analyze organizational performance and key business metrics.</p><p> Created interactive reports using DAX measures, calculated columns, Power Query, filters, slicers, drill-downs, and visualizations.</p><p> Developed business KPIs and analytical measures based on requirements from business stakeholders.</p><p> Connected Power BI to SQL Server data warehouse tables and views and developed optimized semantic models.</p><p> Performed data cleansing and transformation using Power Query before loading data into Power BI models.</p><p> Implemented appropriate relationships between fact and dimension tables and maintained star-schema-based Power BI data models.</p><p> Developed complex DAX calculations for aggregations, time-based analysis, percentages, trends, and business KPIs.</p><p> Performed source-to-target validation and reconciliation between SAP source data and SQL Server warehouse data.</p><p> Troubleshot data discrepancies, report issues, incorrect calculations, and data-refresh failures.</p><p> Optimized SQL queries and Power BI models to improve report performance and data-refresh efficiency.</p><p> Worked closely with business users and SMEs to gather requirements, clarify KPIs, validate reports, and incorporate feedback.</p><p> Participated in UAT, report validation, deployment, and production support activities.</p><p> Created technical and functional documentation covering data mappings, report specifications, business rules, and Power BI dashboards.</p><p> Supported migration from legacy SAP reporting to the SQL Server-based reporting platform, enabling centralized and standardized business reporting.</p><p> Provided production support and analyzed issues related to data loads, SQL Server datasets, Power BI refreshes, and report performance.</p><p> Collaborated with data engineering, database, SAP, and business teams to ensure successful delivery of reporting solutions.</p>