Vijay Yeturi

Results-driven Azure Data Engineer with 3+years of experience designing and implementing scalable data solutions using modern cloud platforms and big data technologies. Proven expertise in building end-to-end data pipelines, optimizing performance, and ensuring high data quality across enterprise systems. Strong background in data warehousing, data lakes, and real-time data processing.

Adept at collaborating with stakeholders to translate business needs into technical solutions. Passionate about leveraging data engineering best practices to enable advanced analytics and business intelligence.

Data Visualization Specialist - Quicknify Software Technologies Private Ltd

(2025-09)

Client: Unilever

• Collaborated with business stakeholders, product owners, and architects to gather requirements and design scalable data platforms using Azure, ADF, Databricks, ensuring alignment with business goals.
• Designed, developed, and maintained ETL/ELT pipelines using Azure Data Factory (ADF) and Databricks, enabling ingestion, transformation, and loading of high-volume structured and unstructured data from enterprise sources.
• Implemented distributed data processing using Synapse Analytics, Spark Pools, and Microsoft Fabric, ensuring high-performance transformations, optimized execution plans, and integration across enterprise data systems.
• Developed data transformation logic using Python and PySpark, leveraging DataFrames, lazy evaluation, caching, and partitioning techniques to process large-scale datasets and improve pipeline performance.
• Built and managed Data Lake and Delta Lake architectures on ADLS, implementing ACID transactions, schema evolution, time travel, and partitioning strategies to ensure data consistency and reliability across environments.
• Integrated external data sources using REST APIs, implementing pagination handling, retry logic, rate limit management, and error handling mechanisms to ensure consistent and fault-tolerant data ingestion processes.
• Implemented data governance using Microsoft Purview and Unity Catalog, enabling data lineage tracking, role-based access control, auditing, and maintaining documentation for compliance and data quality standards.
• Developed dashboards and reports using Power BI, transforming datasets into visual insights, enabling stakeholders to monitor KPIs and make data-driven strategic decisions effectively.
• Automated deployment and release processes using Azure DevOps, CI/CD pipelines, ARM templates, and Databricks Asset Bundles, ensuring consistent code promotion across environments.
• Provided production support by monitoring pipelines using Azure Monitoring, troubleshooting failures, resolving incidents, and optimizing workflows to ensure high availability, reliability, and performance of data solutions.

Data Analyst - Quicknify Software Technologies Private Ltd

(2023-01 - 2023-11)

Client: Hexaware Technologies

• Gathered and analyzed business requirements from stakeholders and translated them into scalable data engineering solutions using Azure Data Factory and Databricks, ensuring seamless data integration systems.
• Designed and implemented high-performance ETL pipelines using ADF and Databricks, integrating data from sources like CosmosDB, S3, Redshift, and CRM systems, enabling centralized analytics and reporting capabilities.
• Developed data transformation workflows using PySpark and SQL, implementing joins, aggregations, window functions, and data cleansing techniques to ensure high-quality consistent datasets for downstream applications.
• Utilized Apache Airflow for orchestrating complex workflows, managing dependencies, scheduling jobs, and ensuring reliable execution of pipelines with proper monitoring and alerting mechanisms.
• Implemented scalable storage solutions using ADLS and Delta Lake, leveraging schema enforcement, version control, and incremental data loading to improve performance and maintain historical data accuracy.
• Integrated third-party systems using REST APIs, handling authentication, rate limiting, retries, and failure scenarios to ensure robust and fault-tolerant ingestion of external datasets into the data platform.
• Applied data governance and security practices using Unity Catalog, implementing fine-grained access control, auditing, and compliance policies to protect sensitive enterprise data and ensure regulatory adherence.
• Developed interactive dashboards using Power BI, enabling business users to analyze trends, monitor KPIs, and derive actionable insights from large, complex enterprise datasets in real time and effectively.
• Automated build and deployment processes using Azure DevOps and CI/CD pipelines, ensuring efficient release management, version control, and environment consistency across development and production systems.
• Monitored and optimized data pipelines, identifying bottlenecks, improving execution times, and ensuring high availability and reliability of data workflows across cloud environments and production systems.

Azure Data Engineer - Quicknify Software Technologies Private Ltd

(2022-02 - 2022-12)

Client: Mu Sigma

• Collaborated with business and technical teams to gather requirements and design ETL workflows for integrating enterprise data from SAP BW and SAP BO into modern Azure-based data platforms.
• Developed and maintained ETL pipelines using SSIS, Azure Data Factory, and Databricks, ensuring seamless data migration, transformation, and integration across legacy and cloud-based enterprise systems.
• Designed and implemented data models using Azure SQL Database and SSAS, enabling efficient OLAP operations and supporting analytical reporting requirements across business domains and enterprise systems.
• Built scalable data transformation processes using Python and PySpark, optimizing large-scale data processing using partitioning, caching, and efficient execution strategies across distributed systems.
• Implemented Data Lake and Delta Lake solutions using ADLS, enabling scalable storage, improved query performance, and reliable data management across structured and semi-structured datasets.
• Optimized SQL queries using indexing, partitioning, and query tuning techniques to improve performance and reduce execution time for large data processing workloads in enterprise environments.
• Developed Power BI business intelligence reports and dashboards, enabling stakeholders to visualize and analyze enterprise data effectively for strategic decision-making purposes across multiple business domains.
• Used Git for version control, enabling collaborative development, code management, and maintaining proper versioning of ETL pipelines and data engineering workflows across distributed teams.
• Participated in deployment and release activities, ensuring smooth migration of ETL pipelines across environments with minimal downtime and operational disruptions in production systems.
• Implemented data governance using Microsoft Purview and Unity Catalog, enabling data lineage tracking, role-based access control, auditing, and maintaining documentation for compliance and data quality standards.
• Developed dashboards and reports using Power BI, transforming datasets into visual insights, enabling stakeholders to monitor KPIs and make data-driven strategic decisions effectively.
• Automated deployment and release processes using Azure DevOps, CI/CD pipelines, ARM templates, and Databricks Asset Bundles, ensuring consistent code promotion across environments.
• Provided production support by monitoring pipelines using Azure Monitoring, troubleshooting failures, resolving incidents, and optimizing workflows to ensure high availability, reliability, and performance of data solutions.

BI Developer - Quicknify Software Technologies Private Ltd

(2021-02 - 2022-01)

Client: Coforge

• Worked closely with stakeholders to gather reporting and analytics requirements, designing scalable data solutions using SSIS, SQL Server, and Power BI to support enterprise reporting needs.
• Developed ETL workflows using SSIS, enabling efficient extraction, transformation, and loading of data from multiple sources into centralized data warehouses and reporting systems for enterprise analytics.
• Designed and deployed reports using SSRS, Power BI, and Tableau, providing interactive dashboards and operational reports for business users across different departments and functional teams globally.
• Built multidimensional data models using SSAS, enabling advanced analytics and improving performance of complex analytical queries across large enterprise datasets and reporting systems.
• Performed data cleansing, transformation, and validation to ensure high data quality, consistency, and accuracy across multiple enterprise data sources and business systems in production environments.
• Integrated data from SAP systems, enabling unified reporting and analytics by combining enterprise resource planning data with other business datasets across organization-wide platforms globally.
• Used Alteryx for data preparation and advanced analytics workflows, improving efficiency in data blending, transformation, and processing activities across multiple business domains effectively and efficiently.
• Optimized SQL queries and ETL workflows to improve performance, reduce execution time, and handle large-scale data processing efficiently in high-volume production environments consistently and reliably.
• Provided production support and maintenance, troubleshooting data issues, optimizing pipelines, and ensuring consistent performance and reliability of data engineering solutions across environments.

Masters - International Project Management with Extended Professional Practice - Coventry University

Bachelor of Technology - Electronics and Communication Engineering