Rahul Reddy Vemula Email & Phone Number

• Designed and implemented data flow processes using SQL and Python, ensuring seamless data integration across systems.• Designed and optimized data pipelines in GCP and AWS using services like Google Cloud Dataflow, AWS Glue, and Lambda, enabling efficient ETL processes for large-scale datasets.• Developed advanced analytics and reporting solutions on GCP's BigQuery and AWS Redshift, utilizing SQL and Python to extract insights from complex data sets while ensuring cost-effective query performance.• Developed and maintained ETL pipelines across Oracle Databases, SAP HANA, and BigQuery environments, automating data workflows and ensuring data integrity across systems.• Integrated Oracle Databases, SAP HANA, and BigQuery with cloud platforms, enhancing the interoperability of data pipelines and enabling seamless access to external data sources.• Automated routine report generation using SQL and Business Objects, reducing manual report generation time by 30% and increasing data accuracy.• Developed Python and SQL-based automation scripts to streamline data extraction and transformation tasks across Oracle, SAP HANA, and BigQuery environments, increasing overall efficiency.• Developed and maintained database schemas, data models, and entity-relationship diagrams to support business requirements, while ensuring optimal database design and minimizing redundancy.• Implemented robust data security measures within Looker, including row-level security and user permissions, to ensure that data access aligns with organizational policies and compliance requirements.• Collaborated with cross-functional teams to gather business requirements and translate them into scalable Looker reports and dashboards, delivering data-driven insights to support strategic decision-making.

New York, New York, United States

• Developed and enforced data quality checks within the ETL pipelines, ensuring accuracy and completeness during data synchronization with Snowflake.• Analyzed and interpreted data quality trends, providing recommendations to improve data governance and reduce data inconsistencies.• Employed GCP IAM and AWS IAM to manage user permissions and roles, ensuring that data access policies were strictly enforced and aligned with organizational security requirements.• Utilized GCP's BigQuery ML and AWS SageMaker for machine learning model development and deployment, leveraging cloud-native tools to perform advanced predictive analytics on large datasets.• Monitored and optimized cloud resource usage in GCP and AWS through tools like Google Cloud Monitoring and AWS CloudWatch, ensuring performance efficiency and cost-effectiveness across cloud environments.• Implemented materialized views and summary tables in Oracle Databases to optimize frequently accessed reports and reduce the processing time for complex queries.• Collaborated with business stakeholders to define data requirements and built custom reporting solutions in SAP HANA and BigQuery, delivering actionable insights for decision-making.• Analyzed large datasets to identify trends and business opportunities, delivering actionable insights that contributed to a 15% increase in revenue for a targeted business unit.• Enhanced reporting capabilities in Tableau by integrating external data sources, creating more comprehensive views of business performance.• Optimized SQL queries embedded in LookML to enhance performance, ensuring that large datasets were queried efficiently, reducing load times, and improving user experience.

• Developed and maintained ETL pipelines across Oracle Databases, SAP HANA, and BigQuery environments, automating data workflows and ensuring data integrity across systems.• Integrated Oracle Databases, SAP HANA, and BigQuery with cloud platforms, enhancing the interoperability of data pipelines and enabling seamless access to external data sources.• Conducted data quality checks and validation in SAP HANA and BigQuery to ensure the accuracy and reliability of datasets used for business analytics and reporting.• Automated the deployment of cloud infrastructure for data analytics using Infrastructure as Code (IaC) tools such as Terraform and AWS CloudFormation, ensuring consistency and reducing manual setup time.• Integrated GCP, Azure, and AWS analytics services like Google Cloud AI, Azure Machine Learning, and AWS SageMaker to build and deploy machine learning models on cloud-based data, facilitating advanced analytics and predictive modeling.• Identified and documented Functional/Non-Functional and other related business decisions for implementing Actimize-SAM to comply with AML Regulations. • Developed Shell scripts for running IBM InfoSphere DataStage Jobs and transferring files to other internal teams and External vendors.• Authoring Python (PySpark) Scripts for custom UDF’s for Row/ Column manipulations, mergers, aggregations, stacking, data labeling and for all Cleaning and conforming tasks.• Create data pipeline of gathering, cleaning, and optimizing data using Hive, Spark.

Hyderabad, Telangana, India

● Designed DTS/SSIS packages to transfer data between servers and load data into databases.● Collaborated with DevOps teams to enhance CI/CD pipelines, ensuring seamless integration with microservices architecture.● Conducted thorough code reviews with a focus on security practices, ensuring adherence to secure coding standards.● Conducted comprehensive reviews of current data states, identifying gaps, and proposing opportunities for enhancing data collection, storage, and analysis processes.● Collaborated with business users to create custom reports in Power BI, tailored to meet specific operational requirements.● Created standard operating procedures (SOPs) for data-driven products, ensuring consistent and efficient operations.● Enhanced data quality through rigorous validation checks, reducing errors and improving overall data accuracy.● Provided stakeholders with regular reports and insights on data quality and system performance, utilizing Tableau for visualization.● Facilitated discussions between business and IT teams to improve data interoperability and streamline data exchange processes.● Implemented ETL processes using SQL Server Integration Services (SSIS), ensuring efficient and accurate data migration.● Developed and maintained metadata documentation in Collibra, improving data transparency and traceability across the organization.