Vishwas Naik
Data Engineer @FEV Europe GmbH
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WORK HISTORY
Data Engineer @FEV Europe GmbH
Aachen, DE
EDUCATION
Bauhaus-Universität Weimar
Master of Science - MS, Digital Engineering
J S S Academy of Technical Education, BANGALORE
Bachelor of Engineering - BE, Mechanical Engineering
Alva's College of Education
Pre University, Science
ABOUT VISHWAS NAIK
I am a technically adept and analytically driven versatile professional with a strong foundation in Mechanical Engineering and advanced competencies in Data Engineering.Originally from India, I completed my Bachelor\'s degree in Mechanical Engineering and gained valuable hands-on experience in the field for over two years. Here I contributed to the calibration and validation of ECU and DCU systems in compliance with BS6 and EU6 emission norms, gaining first-hand experience with time-series data analysis, cross-functional collaboration, and embedded software deployment in automotive systems. However, my passion for innovation and technology led me to pursue higher education at Bauhaus University in Germany. Since then, I have embraced the exciting realm of Data Engineering, where I currently thrive.My professional experience spans both embedded systems engineering and large-scale data engineering projects. At FEV Europe GmbH, I architected and deployed scalable ETL pipelines using Apache Airflow and Python to process vehicle telemetry data, integrated unsupervised learning models such as DBSCAN and K-Means for anomaly detection, and visualized actionable insights through Power BI dashboards.My technical skill set includes proficiency in Python, SQL, Apache Spark, Airflow, and machine learning frameworks such as Scikit-learn and TensorFlow. I am experienced with diverse database systems including MongoDB and PostgreSQL, and I leverage platforms like AWS and Azure for cloud-based data solutions.With a demonstrated ability to translate complex data into meaningful insights and a continuous commitment to learning and innovation, I aspire to contribute to data-centric organizations where engineering rigor meets strategic impact. I excel in operating within agile, iterative processes and have a proven track record of applying machine learning algorithms and statistical techniques to solve loosely defined business problems. I thrive in collaborative environments and am adept at fostering synergy within diverse teams, ensuring effective communication and the delivery of impactful results.Let’s connect and explore how we can collaborate on data-driven innovation.
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