Manish Wagh

Backend Developer

DNV GL•  September 2021 - June 2024•  Pune, Maharashtra

Enhanced Backend Processes: leveraged Python, R, and Oracle SQL to streamline and automate backend workflows, improving operational efficiency and reducing errors. Developed Automated Solutions: Built scalable backend systems, implemented DevOps practices using Docker, Kubernetes, and Terraform, and created automation using Python and VBA. Data Processing and Analysis: Utilised Python, Oracle SQL, and the ELK stack to handle and analyse large datasets, extracting valuable insights that optimised system performance and database efficiency. Forecasting System Support: Designed and maintained backend functionalities for forecasting applications, incorporating orchestration tools like Apache Airflow and AWS for seamless operations. Memory and Database Optimisation: Applied techniques for memory management, distributed systems, and database optimisation (PostgreSQL, Oracle SQL), ensuring high-performance data access and processing. Scalable Architectures: Developed scalable architectures leveraging DevOps practices, orchestrating microservices using Kubernetes, and ensuring system resilience in distributed environments. Testing and Development: integrated Test-Driven Development (TDD) methodologies and implemented CI/CD pipelines, improving code quality and deployment speed. Selenium and Trino/Spark Integration: automated testing and data processing pipelines using Selenium and Trino/Spark for faster insights and validation processes. Server/Application Optimisation: focused on optimising Unix/Linux server performance and application workloads, leveraging Prometheus for monitoring and optimisation insights. Projects: Infrastructure Automation and Monitoring: Designed an automated infrastructure setup using Terraform, Kubernetes, and AWS, integrated with Prometheus for monitoring. The project reduced deployment times by 40% and enhanced system reliability. Real-Time Data Processing System: Developed a distributed data processing system using Apache Spark and Trino, optimised for real-time analytics on large datasets. This system was used to process and analyse construction project data, significantly improving decision-making speed. Scalable Microservices Architecture: Architected a scalable microservices-based system using Docker, Kubernetes, and Airflow for task orchestration, ensuring seamless operations across distributed systems with a focus on clean code practices.