Naga Reddaiah

Azure Data Engineer with 4 years of experience delivering enterprise-grade data solutions, collaborating with business teams, translating requirements into technical designs, and ensuring implementation of scalable data platforms. Strong expertise in Azure Databricks, ADF, Synapse, Fabric, ADLS, Delta Lake, and Snowflake, building robust ETL/ELT pipelines and modern cloud-based data architectures for large-scale enterprise organizations efficiently Proficient in Python, PySpark, SQL, Spark SQL, and performance tuning techniques, optimizing distributed processing, reducing latency, and improving overall data pipeline efficiency and scalability significantly. Experienced in designing Data Warehouse, OLTP, OLAP, Data Lake, and Delta Lake architectures, implementing dimensional modeling, medallion architecture, and enterprise analytics solutions for business intelligence.

Skilled in delivering advanced analytics solutions using Power BI, Tableau, SSRS, Excel, Looker, and Qlik, enabling data-driven decision-making through interactive dashboards and reporting systems effectively. Strong knowledge of data governance, Microsoft Purview, Unity Catalog, metadata management, auditing, and compliance frameworks, ensuring secure and well-managed enterprise data environments.

Azure Data Platform Developer at Habitat UK (2025-05 – 2026-09)

• Partnered with cross-functional teams to understand evolving business requirements and translated them into scalable cloud architecture using Azure services for enterprise-level data modernization initiatives successfully.
• Designed and implemented reusable ingestion frameworks using ADF pipelines, enabling automated data movement from multiple operational systems into centralized analytical platforms with minimal manual intervention.
• Built high-performance data processing workflows using Databricks, optimizing distributed compute clusters to handle large-scale datasets with improved execution speed and reduced resource consumption significantly.
• Developed complex transformation logic using PySpark, implementing advanced joins, aggregations, and window functions to efficiently process structured and semi-structured enterprise datasets at scale.
• Architected robust Data Lake and Delta Lake solutions supporting bronze, silver, and gold layers to ensure data consistency, reliability, and optimized analytical performance across enterprise workloads.
• Integrated enterprise APIs with data pipelines, handling authentication mechanisms, throttling limits, retry policies, and error recovery strategies for uninterrupted data ingestion operations and improved system resilience.
• Implemented enterprise governance frameworks using Unity Catalog, enabling centralized metadata management, fine grained access control, and lineage tracking across multiple data domains and business environments.
• Developed interactive reporting dashboards using Power BI, enabling stakeholders to monitor KPIs, analyze trends, and gain actionable insights from enterprise datasets effectively and in real time for better decision-making.
• Established CI/CD pipelines using Azure DevOps, automating build, test, and deployment processes to ensure faster, consistent, and more reliable delivery of data engineering solutions across environments.
• Supported production environments by monitoring workflows, analyzing failures, performing root-cause analysis, and ensuring stable, continuous operation of enterprise-grade data pipelines and analytics systems.

Data Engineer at Infoline Systems (Client: Sun Life Financials) (2022-12 – 2024-04)

• Engaged with business stakeholders to gather analytical requirements and design scalable Azure-based data engineering solutions aligned with enterprise data modernization goals and reporting needs, ensuring improved decision-making.
• Built orchestration frameworks using ADF and Databricks, enabling seamless scheduling, dependency management, and automation of complex data ingestion pipelines across hybrid environments with enhanced reliability and control.
• Developed scalable transformation pipelines using Databricks, improving processing efficiency for large datasets through optimized Spark configurations and distributed computing techniques for high-performance data processing.
• Implemented advanced data transformations using Python, ensuring clean, structured, and optimized datasets for downstream analytics and business intelligence applications with improved data quality and consistency.
• Designed and maintained Delta Lake architectures, enabling ACID compliance, version control, and efficient handling of evolving enterprise datasets for analytical workloads with strong reliability and scalability.
• Integrated cloud data sources including Legacy and Web applications, enabling cross-platform data synchronization and unified enterprise analytics capabilities across multiple heterogeneous cloud environments with high efficiency.
• Implemented governance standards using Unity Catalog, ensuring secure access, metadata tracking, and compliance across enterprise-wide data assets with improved data governance and audit readiness.
• Built enterprise dashboards using Power BI, providing executives and analysts with real-time insights into business performance and operational metrics for strategic reporting and analysis across organizations.
• Automated deployment pipelines using Azure DevOps, ensuring consistent delivery of data solutions across development, staging, and production environments with streamlined release management processes.
• Monitored production systems, optimized pipeline performance, resolved data issues, and ensured continuous availability of enterprise data platforms and workflows for uninterrupted business operations.

Data Engineer at Infoline Systems (Client: Canadian Utilities) (2022-03 – 2022-12)

• Collaborated with SAP business teams to analyze reporting requirements and design scalable Azure data engineering solutions supporting enterprise analytics and decision-making processes across complex global business environments.
• Developed ETL workflows using ADF and SSIS, enabling structured integration of SAP BW, SAP BO, and enterprise data systems into centralized repositories with improved consistency, accuracy, and data reliability across platforms.
• Built distributed data processing jobs using Databricks, improving scalability and reducing processing time for large enterprise datasets significantly through optimized Spark configurations and efficient cluster resource utilization.
• Implemented transformation logic using PySpark and SQL, handling complex business rules and ensuring optimized data processing across multiple datasets for accurate, high-quality, and performance-driven analytical outputs.
• Designed scalable Data Lake and Delta Lake solutions, ensuring structured data storage, historical tracking, and optimized query performance for analytics workloads across enterprise-grade reporting and BI systems.
• Integrated SAP systems using connectors and pipelines, ensuring reliable extraction, transformation, and loading of enterprise data into cloud environments with secure, efficient, and automated data movement processes.
• Developed OLAP models using SSAS, enabling multidimensional analysis and fast query performance for business intelligence reporting systems supporting strategic planning, forecasting, and executive decision-making.
• Created interactive dashboards using Power BI, delivering actionable insights from SAP and operational datasets for business stakeholders with real-time visibility into KPIs and performance metrics across enterprise operations.
• Managed version control and collaboration using Git, ensuring structured code management, branching strategies, and smooth deployment across multiple environments with controlled and reliable release cycles.
• Provided production support by monitoring ETL workflows, resolving failures, and ensuring uninterrupted operation of enterprise reporting systems with high availability, stability, and proactive issue resolution.

Masters – Northumbria University, London, UK (2025)

Bachelors – Saveetha Engineering College, Chennai, India (2022)