Bhargav K

Developed and scaled backend systems using Python, ensuring seamless data ingestion, processing, and integration with machine learning workflows. Leveraged Kubernetes and Docker to orchestrate and deploy containerized workloads, achieving high availability and consistent performance in cloud environments. Developed and optimized ETL pipelines using Python, PySpark, Snowflake and Databricks to process and transform large datasets, ensuring high performance and scalability for product development initiatives. Implemented complex SQL queries and data models to support analytical and operational use cases, driving data consistency and accessibility across the product lifecycle. Streamlined data workflows by building automated pipelines on cloud, integrating diverse data sources, and enabling seamless collaboration across the Product Engineering Team. Collaborated with cross-functional teams to design and deliver scalable data solutions, leveraging Databricks for real-time data processing and insights generation. Ensured data quality and compliance by conducting thorough validation and implementing best practices in data governance, aligning with project goals and timelines.

Developed a scalable backend platform using Python to optimize loan processing and fraud detection, enabling efficient data ingestion, transformation, and real-time analytics. Designed RESTful APIs for seamless interaction between distributed systems and analytics workflows, and implemented containerized deployments using Docker and Kubernetes on Azure and GCP. Built and optimized CI/CD pipelines with Azure DevOps and Jenkins, automating testing, deployment, and monitoring to ensure high performance and reliability. Integrated data pipelines with Azure Data Factory, Databricks, and Snowflake, processing transactional data for advanced analytics, while ensuring compliance with standards through secure data management practices.

Developed and automated ETL workflows using SQL Server Integration Services (SSIS) to integrate data from transactional systems, CRM platforms, and website analytics into a centralized data warehouse. Designed and optimized data warehouse solutions on SQL Server to support marketing data storage, customer segmentation, and campaign performance analysis, enhancing decision-making. Implemented SQL Server Reporting Services (SSRS) for automated reporting, delivering insights on campaign ROI, conversion rates, and customer retention while ensuring unified and consistent reporting. Migrated marketing data from legacy systems to SQL Server and optimized ETL processes, achieving a 30% reduction in batch processing time while ensuring compliance with GDPR and marketing regulations.

Experienced Data Engineer Consultant specializing in database migration projects, successfully migrating complex datasets from legacy systems to modern platforms ensuring minimal downtime and data integrity throughout the migration process. Expertise in SQL development for data transformation, migration, and optimization, designing and implementing high-performance queries, stored procedures, and database structures to ensure seamless data handling during migration. Proficient in creating and managing data pipelines to automate migration workflows, improve efficiency, and ensure compliance with data governance standards, ensuring a smooth transition to cloud architectures. Collaborated with cross-functional teams to assess, plan, and execute migration strategies, ensuring that business-critical data was migrated accurately, on time, and aligned with project goals while optimizing data storage and performance.