Vinya Peketi

Microsoft Certified Data Engineer and Business Intelligence Engineer with 5+ years of experience designing, developing, and optimizing enterprise-scale data platforms, cloud-based ETL/ELT pipelines, and business intelligence solutions using Microsoft Azure, Microsoft Fabric, Azure Databricks, Snowflake, DBT, SQL Server, and Power BI. Extensive experience building scalable data ingestion frameworks, modern Lakehouse architectures, enterprise data warehouses, and interactive dashboards that support data-driven decision making. Hands-on expertise in developing high-perfor006Dance data pipelines using Azure Data Factory, Microsoft Fabric Data Factory, Azure Databricks, PySpark, Spark SQL, Snowflake, and DBT, while implementing Medallion Architecture, Delta Lake, incremental processing, Change Data Capture (CDC), and dimensional modeling. Strong background in SQL Server performance tuning, Databricks optimization, query optimization, and cloud migration initiatives. Experienced in partnering with business stakeholders, solution architects, analysts, and cross-functional teams to gather requirements, design scalable data solutions, automate reporting, improve data quality, and deliver enterprise BI solutions using Agile methodologies. Microsoft Certified in Azure Fundamentals (AZ-900) and Azure Administrator (AZ-104) with strong expertise across Azure Data Engineering, Microsoft Fabric Analytics, and Business Intelligence.

• Agile
• Amazon Web Services
• Angular
• Attention to detail
• Business analysis
• Communication
• CSS
• Customer service
• Data analysis
• Data entry
• Data Validation
• Data visualization
• English
• Git
• GitHub
• Google Cloud
• HTML
• Java
• JavaScript
• Jira
• Kubernetes
• Leadership
• Microsoft Azure
• Microsoft Excel
• Microsoft Office
• Microsoft Word
• MongoDB
• MySQL
• Organization
• PostgreSQL
• Power BI
• Problem solving
• Product management
• Project management
• Python
• Quality assurance
• Scrum
• SQL
• Tableau
• Teamwork
• Time management

1. Data & BI Engineer

   Enercare

   May 2025 to Present

   Canada

   Environment: Microsoft Azure, Microsoft Fabric, Azure Data Factory, Fabric Data Factory, Azure Databricks, PySpark, Spark SQL, SQL Server, Azure Synapse Analytics, Snowflake, DBT, Power BI, DAX, Power Query, Azure DevOps, Git, Delta Lake, OneLake, Azure SQL Database, Azure Data Lake Storage Gen2, CI/CD, Agile. • Designed, developed, and maintained enterprise-scale data engineering solutions using Microsoft Azure and Microsoft Fabric, supporting business intelligence, analytics, and operational reporting initiatives. • Developed scalable ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric Data Pipelines, Azure Databricks, and Snowflake to ingest structured and semi-structured data from multiple enterprise source systems. • Built and maintained Lakehouse architecture using Microsoft Fabric OneLake, implementing bronze, silver, and gold layers following Medallion Architecture principles to improve data reliability and governance. • Designed high-performance PySpark and Spark SQL notebooks for cleansing, transforming, validating, and enriching large-scale datasets containing millions of records. • Developed reusable DBT models, incremental transformations, snapshots, and automated data quality tests to standardize business logic and improve maintainability across analytical data models. • Implemented incremental loading strategies and Change Data Capture (CDC) frameworks, significantly reducing pipeline execution time while minimizing resource consumption. • Built enterprise data warehouse solutions using Snowflake, Azure Synapse Analytics, and Microsoft Fabric Warehouse, enabling scalable reporting and self-service analytics. • Optimized SQL Server stored procedures, complex joins, views, indexing strategies, and execution plans, improving report execution times and reducing database resource utilization. • Performed advanced Databricks performance tuning by implementing partition pruning, broadcast joins, Adaptive Query Execution (AQE), caching strategies, Delta optimization, Z-Ordering, and file compaction, resulting in improved Spark job performance. • Designed dimensional data models using Kimball methodology, including fact tables, dimension tables, Slowly Changing Dimensions (Type 1 & Type 2), and surrogate key implementation. • Integrated data from SQL Server, Azure SQL Database, REST APIs, cloud storage, and flat files into centralized analytical platforms while ensuring data consistency and integrity. • Developed interactive Power BI dashboards, executive scorecards, and KPI reports supporting Finance, Sales, Operations, and Executive Leadership teams. • Created optimized Power BI Semantic Models, DAX measures, calculated columns, and Power Query transformations to enhance report performance and enable self-service analytics. • Implemented Row-Level Security (RLS), workspace governance, dataset optimization, and refresh scheduling within Power BI Service to ensure secure access to business-critical reports. • Automated recurring ETL workflows and report refresh processes using Azure Data Factory triggers, Fabric Pipelines, and Azure DevOps CI/CD pipelines, reducing manual effort and improving operational efficiency. • Implemented Git-based source control and Azure DevOps release pipelines for automated deployment across Development, QA, UAT, and Production environments. • Monitored production pipelines, investigated failures, resolved data quality issues, and implemented proactive monitoring to improve platform stability and minimize business disruption. • Mentored junior developers on SQL best practices, PySpark development, Microsoft Fabric implementation, Power BI optimization, and coding standards to improve overall team productivity.

2. Consultant

   Capgemini

   Jun 2019 to Aug 2023

   India

   Environment: Azure Data Factory, Azure Databricks, SQL Server, Azure Synapse Analytics, Azure SQL Database, Microsoft Fabric, Power BI, PySpark, Spark SQL, Python, Snowflake, DBT, Azure DevOps, Git, Delta Lake, Azure Data Lake Storage Gen2, CI/CD, Agile. • Designed, developed, and maintained enterprise ETL pipelines using Azure Data Factory and Azure Databricks to ingest data from SQL Server, Azure SQL Database, APIs, flat files etc into centralized analytics platforms. • Developed scalable PySpark and Spark SQL applications to transform, cleanse, standardize, and validate large datasets for reporting and advanced analytics. • Built reusable data transformation frameworks using SQL, Python, and DBT, improving development consistency and reducing maintenance effort across multiple projects. • Designed and optimized dimensional data models including fact tables, conformed dimensions, SCD (SCD Type 1 & Type 2), and surrogate key management following Kimball best practices. • Performed SQL Server performance tuning using execution plans, indexing strategies, statistics updates, query optimization, and partitioning techniques to improve application performance. • Built scalable data ingestion frameworks supporting incremental loads, CDC processes, and metadata-driven ETL architecture. • Integrated Snowflake into enterprise data pipelines for analytical processing and developed optimized SQL transformations to support business reporting. • Developed DBT models including staging, intermediate, and presentation layers while implementing automated testing and documentation. • Implemented Databricks optimization techniques including partition pruning, broadcast joins, caching, Adaptive Query Execution (AQE), and Delta file optimization to improve Spark job execution performance. • Created reusable Azure Data Factory pipeline templates using parameters and dynamic expressions to simplify deployment and reduce code duplication. • Supported Azure DevOps CI/CD implementations by managing repositories, pull requests, build pipelines, release pipelines, and automated deployments across Development, QA, and Production environments. • Participated in Agile development activities including sprint planning, estimation, daily stand-ups, sprint reviews, retrospectives, and code reviews.

1. Lambton College

   Post Graduate Certificate, Cloud Infrastructure and Administration

   Ontario, Canada

   2025

2. Malla Reddy Engineering College

   Bachelor of Technology, Computer Science Engineering

   India

   2019

• Microsoft Certified: Azure Fundamentals (AZ-900)

  Microsoft

• Microsoft Certified: Azure Administrator Associate (AZ-104)

  Microsoft