Led a team of 6 big data engineers in developing a global big data platform utilizing technologies such as Python, Apache Hadoop, Apache Spark, Apache Impala, Hive, and Apache Airflow. Implemented the Data Vault 2.0 model for a Data Lakehouse. Managed deployments of micro-services using Docker across Development, Staging, and Production environments. Enhanced and debugged Hadoop jobs, and developed CI/CD pipelines using Jenkins, BitBucket, and SonarQube. Created data pipeline frameworks as Python libraries and established a comprehensive big data microservices pipeline.

Collaborated with a global team to design stable, reliable, and effective databases using Data Vault 2.0 for the Enterprise Data Warehouse at Robert Bosch GmbH. Developed a data framework using Python to populate the data warehouse. Engaged with users to gather requirements and identify new features. Resolved database usage issues and malfunctions, modified databases as per requests, and conducted tests. Worked on optimizing and maintaining legacy systems while coaching and assigning tasks to new team members.

Developed and maintained a highly scalable and extensible Big Data platform aimed at enabling the collection, storage, modeling, and analysis of massive data sets from multiple channels. Created and upheld scalable and reliable data pipelines for ingesting data from diverse data sources into the Data Lake. Ensured data adherence to quality standards and optimal formats, facilitating swift access for downstream users. Developed both big data and batch/real-time analytical solutions leveraging emerging technologies.

This project involved the full lifecycle of Robotic Process Automation (RPA), including the development, deployment, and maintenance of automated processes to achieve targeted business benefits and return on investment. The platform's infrastructure and application were maintained to ensure robust operational capabilities. The project required effective stakeholder engagement across the business to manage dependencies and ensure successful automation delivery. Continuous improvement of automated processes was conducted to optimize performance and maximize benefits for the organization.

This project involved creating and defining robot workflows based on customer business processes to automate daily tasks. The workflows were optimized to enhance performance and involved building automation tools and robotic process automation solutions. Additionally, a dashboard was developed using Power BI for the customer.

Conducted comprehensive data analysis on wafers to resolve integration issues, enhancing problem-solving efficiency for the team. Developed automation tools and reports, overseeing the maintenance of an internal web portal. Gained experience as a yield engineer during the internship period.