Vamsi Krishna Bhadragiri Email and Phone Number
I'm a dedicated and experienced Splunk Admin, and Data Scientist with a strong passion for turning data into actionable insights. With a deep understanding of Splunk architecture and a proven track record of successful deployments, I thrive in configuring, optimizing, and troubleshooting Splunk environments. My expertise lies in driving operational efficiency, ensuring data integrity, and maximizing the value of Splunk for businesses.Splunk:. I have hands-on professional experience in Data-onboarding from various data sources(like AWS, and Kubernetes) . Configuring AWS services with proper IAM roles to export security-related data to Splunk for monitoring.. Well-versed in writing Splunk query. Making data CIM compliant for security use cases (SIEM -Security information and event management). Developing Splunk Dashboard. Implementing Splunk Enterprise and Splunk Products . Creating Splunk custom alerts ((using Splunk Python SDK's). Creating Splunk search commands (using Splunk Python SDK's). Building Splunk apps and Technical Addons(TAs)Cribl:. Building pipelines for data volume reduction, filtering, and data modifications.. Routing data to multiple destinations using pipelines. Administrating Cribl distributed environmentTechnologies:Splunk EnterpriseSplunk ITSISplunk Cloud CriblSplunk ObservabilityAWS
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Data EngineerAldi Süd Jul 2024 - PresentMülheim An Der Ruhr, North Rhine-Westphalia, Germany -
Junior Data Scientist And Splunk ConsultantBridge:Com Sep 2021 - Jun 2024Aachen, North Rhine-Westphalia, Germany -
Master ThesisChair Of Production Engineering Of E-Mobility Components (Pem) May 2019 - Nov 2019Kreisfreie Stadt Aachen Area, GermanyTitle: Development of an adaptive quality management model for agile automotive assembly of E-Vehicles in Industry 4.0 by analyzing production data.Motivation:In order to sustain in the current market, especially the automotive industry. It is important to offer products as per individual requirements. In order to achieve this agile methodology is required. Therefore, this project achieved a methodology for quality management in an effective way that reduces the time for inspection activities, unnecessary flows by utilizing the degree of freedom available in an agile environment (such as Drones, AGV, AR, etc.)• Developed an adaptive quality management model for agile automotive assembly in Industry 4.0 environment• Developed intelligent planning system for inspection activities by analyzing assembly data• Analyzed production data for improvement of inspection activities for reduction of cycle time using agile degrees of freedom -
Project Work/InternChair Of Production Engineering Of E-Mobility Components (Pem) Apr 2018 - Dec 2018AachenTitle: Development of methodology for car door assembly process with modern Laser technology in an agile environment. Motivation: To sustain current market conditions especially automotive, it is necessary to produce products effectively with good quality. Thereby, manufacturing products at high tolerance can be cost-effective at the same time it is necessary to inculcate quality to the product. Therefore this project achieved cost-effective and effective mounting of car door by designing an artificial intelligence model using a deep neural network • Extracted product data by Autodesk Inventor, laser scanner, and transformed the dataset using Python• Performed data analysis for development of adaptive door hinge using Python, Polyworks• Developed adjustable concept for car door hinge by machine learning algorithms and Artificial Neural Network (ANN) -
Internship TraineeZf Group Sep 2017 - Dec 2017Schweinfurt,Germany• Performed data analysis on production data with statistical software using Cornerstone,Minitab, Python• Prepared dataset of production process and carried out statistical data evaluation and visualized the data using Excel and Python• Applied machine learning algorithm for clustering the stainless-steel sheets consideringMechanical and chemical properties -
Junior EngineerHobel Bellows Co. Jul 2014 - Nov 2015Visakhapatnam• Worked on process optimization for Bellows extrusion process using Lean tools and Six sigma methodology. • Extracted production data from multiple sources, cleaned and transformed large datasets using MySQL, Minitab, Python• Reported KPIs to senior management daily by building dashboards for production process• Carried out Design of experiments (DoE) for obtaining optimal parameter of machines• Implemented and refined manufacturing process by applying lean manufacturing principlesto remove bottlenecks and reduce the cycle time of process• Performed the processes simulations (SPC) using MiniTab and MS Excel• Design and development of the production process for bellows production (PPAP, PFMEA)
Vamsi Krishna Bhadragiri Education Details
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Applied AiData Science -
Board Of Intermediate Education1,3
Frequently Asked Questions about Vamsi Krishna Bhadragiri
What company does Vamsi Krishna Bhadragiri work for?
Vamsi Krishna Bhadragiri works for Aldi Süd
What is Vamsi Krishna Bhadragiri's role at the current company?
Vamsi Krishna Bhadragiri's current role is Data Engineer.
What schools did Vamsi Krishna Bhadragiri attend?
Vamsi Krishna Bhadragiri attended Rwth Aachen University, Applied Ai, Jawaharlal Nehru Technological University, Kakinada, Board Of Intermediate Education.
Who are Vamsi Krishna Bhadragiri's colleagues?
Vamsi Krishna Bhadragiri's colleagues are Adrian Rempel, Sven Steiner, Tolunay Sirin, Susanne Schneider, Kinga Glowinska, Halil Okan Köksal, Philipp Melzer.
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