Senior Power BI Developer and Azure Data Engineer

SaiVenkat Rahul Reddy Devarapelly

Sr. Power BI Developer

Email: *******@*****.*** Phone:216-***-****

PROFESSIONAL SUMMARY:

Senior Power BI Developer with 10+ years of experience designing, developing, and optimizing enterprise business intelligence and cloud-based analytics solutions using Power BI, Azure Synapse Analytics, Azure Data Factory, Azure SQL, and Azure Data Lake Storage (ADLS Gen2). Experienced in building scalable ETL/ELT pipelines, developing semantic models, datasets, and dataflows, and creating high-performance dashboards using DAX and Power Query (M). Strong expertise in SQL, T-SQL, query optimization, dimensional data modeling, and processing structured and semi-structured data including JSON, CSV, and Parquet. Hands-on experience integrating data from Azure services, SQL Server, Snowflake, Databricks, and Salesforce while optimizing DirectQuery and Import models, troubleshooting data refresh and pipeline issues, and delivering secure, scalable analytics solutions in Agile environments.

TECHNICAL SKILLS:

Business Intelligence & Visualization: Power BI Desktop, Power BI Service, Power BI Dashboards, Power BI Reports, KPI Reporting, Data Visualization, Drill-Down, Drill-Through, Bookmarks, Dynamic Slicers, Paginated Reports, Report Optimization, Performance Analyzer.

Data Modeling & Analytics: Semantic Models, Data Modeling, Star Schema, Snowflake Schema, Dimensional Modeling, Fact & Dimension Tables, Composite Models, Import Mode, DirectQuery, DAX (Time Intelligence, Context Transition, Variables), Calculated Columns, Measures.

Data Engineering & ETL/ELT: ETL/ELT, Azure Data Factory (ADF), Data Pipelines, Data Ingestion, Data Transformation, Data Cleansing, Data Migration, Data Validation, Data Reconciliation, Power Query (M), SSIS

Cloud & Data Platforms: Azure Synapse Analytics (Dedicated SQL Pools, Serverless SQL Pools), Azure Data Lake Storage

(ADLS Gen2), Azure SQL Database, Microsoft Fabric, OneLake, DirectLake

Database & Querying: Microsoft SQL Server 2022, SQL Server Management Studio (SSMS), SQL, T-SQL, PL/SQL, Complex SQL Queries, Stored Procedures, Views, CTEs, Joins, Query Optimization, Execution Plans, Indexing, Query Folding.

Data Connectivity & Integration: REST APIs, SQL Server, Azure SQL Database, Flat Files, JSON, CSV, Parquet, Structured & Semi-Structured Data, On-Premises Data Gateway, Cloud Data Gateway.

Power BI Advanced Features: Power BI Dataflows, Semantic Models, Incremental Refresh, Aggregations, Partitioning, Reusable Datasets, Dataset Certification, Deployment Pipelines, Row-Level Security (RLS).

Reporting & Analytics Tools: SSRS (SQL Server Reporting Services), Microsoft Excel (Pivot Tables, Charts, VBA), Ad-hoc Reporting

DevOps & Version Control: Azure DevOps, CI/CD Pipelines, Git, Version Control, XMLA Endpoints, PBIP Projects, ALM Toolkit, Tabular Editor, DAX Studio, TFS, SVN

Security & Governance: Row-Level Security (RLS), Access Control, Data Governance, Workspace Administration, Premium Capacity Management, Naming Conventions, Documentation, Compliance Standards

AI-Assisted Development: ChatGPT, Microsoft Copilot, Claude AI, Prompt Engineering, AI-assisted SQL Query Optimization, AI-assisted Code Generation, AI-assisted Documentation, Code Reviews, Debugging

Development Practices & Collaboration: Agile, Scrum, SDLC, Sprint Planning, Backlog Management, Stakeholder Management, Requirements Gathering, Cross-Functional Collaboration, Team Leadership, Mentoring, Production Support, Troubleshooting, Root Cause Analysis

EXPERIENCE:

Finra, Woodbridge, NJ Sr. Power BI Developer

December 2024 - Present

Architected Microsoft Fabric platform leveraging Fabric Lakehouse, OneLake, Direct Lake semantic models, and Fabric Data Warehouse for enterprise-scale analytics.

Designed and optimized scalable ETL/ELT pipelines using Azure Synapse Analytics, Azure Data Factory, SQL Server, and Azure SQL to process 20M+ records daily, improving data availability by 40%.

Developed reusable semantic models, datasets, and dataflows using DAX, Power Query (M), Star Schema design, DirectQuery, Import Mode, and incremental refresh, supporting 150+ enterprise reports while reducing report development effort by 35%.

Established enterprise reporting frameworks, metadata repositories, certified datasets, and visualization standards to support governed self-service BI.

Built enterprise data ingestion and integration workflows using SQL Server, Azure SQL Database, REST APIs, and structured and semi-structured data formats including JSON, CSV, and Parquet.

Led BI modernization initiatives by defining reporting architecture, migration strategy, solution design, and deployment roadmap across enterprise reporting platforms.

Led enterprise Power BI On-Premises Data Gateway upgrades by validating report dependencies, gateway clusters, refresh schedules, and data source connectivity while minimizing production downtime.

Conducted architecture governance reviews, capacity planning, and BI standards implementation while mentoring developers and supporting BI Center of Excellence initiatives.

Configured enterprise Power BI workspaces, Premium Capacity, Row-Level Security (RLS), deployment pipelines, governance standards, and lifecycle management across multiple business units.

Optimized enterprise semantic models using aggregation tables, partitioning, VertiPaq optimization, DAX Studio, Performance Analyzer, and Tabular Editor, reducing report response times by 60% and dataset refresh durations by 45%.

Tuned complex SQL queries, stored procedures, indexes, and ETL processes, reducing pipeline execution time by 50% while improving reporting performance and system reliability.

Troubleshot Power BI dataset refresh failures, gateway connectivity issues, SQL performance bottlenecks, semantic model inconsistencies, and upstream data pipeline failures to ensure high platform availability.

Integrated Microsoft Fabric capabilities including OneLake and DirectLake while leveraging Azure SQL and SQL Server to modernize enterprise reporting architecture and improve data accessibility.

Designed and implemented CI/CD deployment strategies using Azure DevOps, Git, PBIP projects, XMLA Endpoints, Deployment Pipelines, and ALM Toolkit for controlled releases across Development, Test, and Production environments .

Partnered with Finance, Compliance, business stakeholders, and Data Engineering teams to gather reporting requirements, validate KPI calculations, and translate complex business logic into scalable BI and analytics solutions .

Leveraged Microsoft Copilot and Claude AI to optimize SQL queries, automate documentation, perform code reviews, and accelerate BI solution delivery while maintaining enterprise coding standards.

Authored architecture documentation, governance standards, operational runbooks, and knowledge transfer materials to support enterprise Power BI administration and long-term platform maintenance.

Mentored junior developers, conducted code reviews, and promoted best practices in data modeling, performance optimization, Power BI development, and Agile delivery. Environment: Azure Synapse Analytics, Azure Data Factory (ADF), Azure SQL Database, SQL Server, Power BI, Microsoft Fabric, OneLake, DirectLake, DAX, Power Query (M), SSIS, T-SQL, ETL/ELT, REST APIs, JSON, CSV, Parquet, Star Schema, DirectQuery, Import Mode, Incremental Refresh, RLS, Tabular Editor, DAX Studio, Azure DevOps, Git, XMLA Endpoints, ALM Toolkit, Agile Scrum.

Fannie Mae, Washington, D.C. Sr. Power BI Developer January 2021 - November 2024

Modernized legacy mortgage reporting by migrating enterprise reports into scalable Power BI dashboards while preserving complex business rules and improving report usability.

Led migration planning from legacy BI platforms to Power BI, including report inventory, semantic model redesign, KPI validation, deployment strategy, and production rollout.

Designed and optimized ETL/ELT pipelines using Azure Data Factory, SQL Server, and Azure SQL Database to integrate mortgage servicing data for enterprise reporting and analytics.

Developed reusable semantic models, Power BI datasets, and dataflows supporting Finance, Operations, and Risk teams, reducing duplicate development efforts by 30%.

Collaborated with Data Engineering teams to validate transformed datasets, perform source-to-target reconciliation, and ensure high-quality data for Power BI reporting.

Built enterprise data integration workflows using SQL Server, Azure SQL Database, and structured data sources, improving data consistency across multiple mortgage reporting systems.

Optimized SQL queries, stored procedures, report datasets, and ETL processes, reducing report execution times by 45% for high-volume operational reporting.

Configured and maintained Power BI Service, On-Premises Data Gateway, scheduled refreshes, and deployment processes to ensure secure and reliable hybrid connectivity.

Implemented Row-Level Security (RLS), role-based access controls, and enterprise governance standards to support secure and compliant reporting solutions.

Developed drill-through Power BI dashboards and integrated Paginated Reports (RDL) to deliver detailed operational and regulatory reporting capabilities.

Coordinated testing, production deployments, post-production support, and root cause analysis, improving reporting platform stability and reducing production issues by 35%.

Performed end-to-end data validation, KPI reconciliation, and User Acceptance Testing (UAT) with Finance and Operations stakeholders to ensure reporting accuracy.

Utilized Azure DevOps and version control to manage source code, release management, and CI/CD activities across Development, Test, and Production environments.

Automated enterprise reporting workflows and scheduled refresh processes, improving report availability while reducing manual operational effort by 40%.

Authored technical documentation, operational runbooks, and deployment guides while collaborating with QA, Infrastructure, and business teams to streamline reporting operations.

Designed and optimized ETL/ELT pipelines using Azure Synapse Analytics, Azure Data Factory (ADF), SQL Server, and Azure SQL Database to integrate mortgage servicing data for enterprise reporting and analytics.

Built enterprise data integration workflows using Azure Synapse Analytics, Azure Data Lake Storage (ADLS Gen2), SQL Server, Azure SQL Database, and REST APIs, processing structured and semi-structured data including JSON, CSV, and Parquet to improve data consistency across mortgage reporting systems.

Collaborated with Data Engineering teams to validate transformed datasets, perform source-to-target reconciliation, optimize Synapse SQL workloads, and ensure high-quality data for Power BI reporting.

Optimized SQL queries, Synapse SQL workloads, stored procedures, report datasets, and ETL processes, reducing report execution times by 45% for high-volume operational reporting.

Delivered BI solutions in Agile Scrum environments by partnering with cross-functional teams to translate business requirements into scalable Power BI and data integration solutions. Environment: Azure Synapse Analytics, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS Gen2), Azure SQL Database, SQL Server, Power BI, Power BI Service, DAX, Power Query (M), Semantic Models, Dataflows, Star Schema, ETL/ELT, REST APIs, JSON, CSV, Parquet, SSRS, Paginated Reports, Row-Level Security (RLS), On-Premises Data Gateway, Azure DevOps, CI/CD, Stored Procedures, Data Validation, Data Reconciliation, Excel, Agile Scrum. Horizon BCBS, Newark, NJ Power BI Developer

April 2018 - December 2020

Designed and developed interactive Power BI dashboards and executive reports supporting claims processing, reimbursement analysis, provider performance, and healthcare operational KPIs.

Built scalable semantic models, reusable datasets, and DAX measures to support enterprise reporting across Finance, Claims, and Operations teams.

Developed ETL workflows using SSIS, SQL Server, and Azure Data Factory to integrate healthcare data from multiple enterprise systems into centralized reporting solutions.

Developed and optimized data transformation workflows using Power Query (M), improving data quality and reducing manual data preparation efforts by 35%.

Integrated data from SQL Server, Excel, and Azure SQL Database while performing source-to-target mapping, data validation, and reconciliation to ensure reporting accuracy.

Designed Star Schema data models, calculated columns, and complex DAX measures to improve report scalability and analytical performance.

Utilized Import Mode, DirectQuery, and incremental refresh techniques to optimize dashboard performance and support near real-time reporting requirements.

Created parameterized Paginated Reports, drill-through reports, matrix reports, and reusable reporting templates supporting operational, compliance, and regulatory reporting.

Optimized complex SQL queries, stored procedures, views, and report datasets, reducing report execution time by 40% and improving overall reporting performance.

Implemented Row-Level Security (RLS), configured On-Premises Data Gateway, and managed scheduled dataset refreshes to ensure secure and reliable Power BI Service operations.

Collaborated with business analysts and stakeholders to validate KPI calculations, reporting logic, and business requirements prior to production deployment.

Delivered ad-hoc analytics and self-service reporting solutions, improving report turnaround time by 30% and supporting data-driven decision-making.

Applied best practices in data modeling, performance tuning, lifecycle management, and Power BI development to deliver scalable BI solutions.

Collaborated within Agile Scrum teams using TFS and version control to support sprint planning, development, testing, and production releases.

Authored technical documentation, data mapping specifications, and operational support documents while providing production support for enterprise reporting applications. Environment: Power BI Desktop, Power BI Service, DAX, Power Query (M), Azure Data Factory (ADF), Azure SQL Database, SQL Server, T-SQL, SSIS, SSRS, ETL/ELT, Star Schema, Data Modeling, Data Warehousing, Import Mode, DirectQuery, Incremental Refresh, Row-Level Security (RLS), On-Premises Data Gateway, Excel, Data Validation, Data Reconciliation, Agile Scrum, TFS, Version Control.

BNY Mellon, New York, NY BI Developer

July 2016 - March 2018

Collaborated across the full Software Development Life Cycle (SDLC) to gather business requirements, design technical solutions, develop, test, and deploy enterprise BI applications.

Designed and developed enterprise SSRS reports including tabular, matrix, drill-through, parameter-driven, and operational reports supporting Finance and business operations.

Developed and maintained SSIS ETL workflows to integrate, cleanse, and transform data from multiple heterogeneous source systems into the enterprise data warehouse.

Designed Star Schema data warehouse models with fact and dimension tables to support scalable reporting and analytical workloads.

Developed and optimized complex T-SQL queries, stored procedures, views, indexing strategies, and execution plans using SQL Server Management Studio (SSMS), improving query performance by 45%.

Built reusable shared datasets, report models, report subscriptions, and automated report delivery processes, reducing manual reporting effort by 30%.

Performed Source-to-Target Mapping (STM), data profiling, validation, and reconciliation to ensure data quality, consistency, and compliance with business rules.

Optimized ETL workflows, SQL queries, and reporting datasets, reducing report execution time by 35% and improving production reporting reliability.

Integrated data from multiple enterprise systems into centralized SQL Server repositories, supporting consistent reporting across business units.

Conducted root cause analysis and resolved production reporting issues through SQL tuning, ETL enhancements, and data quality improvements.

Provided production support, report enhancements, and performance tuning for enterprise BI applications while maintaining high system availability.

Created Excel-based analytical reports using Pivot Tables, Charts, and VBA macros to automate recurring business reports and ad hoc analysis.

Implemented version control using SVN to manage source code, support collaborative development, and maintain release stability.

Worked closely with business users and QA teams to validate reporting logic, verify KPI calculations, and support User Acceptance Testing (UAT).

Delivered end-to-end BI solutions by combining SQL Server, SSIS, ETL, dimensional modeling, and SSRS reporting technologies to support enterprise decision-making. Environment: SQL Server, T-SQL, SQL Server Management Studio (SSMS), SSIS, SSRS, ETL, Data Warehousing, Star Schema, Stored Procedures, Views, Query Optimization, Indexing, Source-to-Target Mapping, Data Validation, Data Reconciliation, Excel, VBA, SVN, BI Reporting, SDLC.

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