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Pinnacle Infotech
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Data Engineer

Data Engineer

Pinnacle Infotech

3 - 7 years

0 Lacs

durgapur west bengal

Posted:1 day ago| Platform: Shine logo

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Skills Required

python spark sql aws azure gcp docker kubernetes devops mlflow cicd

Work Mode

On-site

Job Type

Full Time

Job Description

You will be joining Pinnacle Infotech, a company that values inclusive growth in an agile and diverse environment. With over 30 years of global experience, 3,400+ experts, and 15,000+ projects completed across 43+ countries for 5,000+ clients, you will have the opportunity to work on impactful global projects. At Pinnacle Infotech, you will experience rapid career advancement, cutting-edge training, and a supportive community that celebrates uniqueness and embraces E.A.R.T.H. values. As an MLOps Engineer, your primary responsibility will be to build, deploy, and maintain the infrastructure required for machine learning models and ETL data pipelines. You will collaborate closely with data scientists and software developers to streamline machine learning operations, manage data workflows, and ensure that ML solutions are scalable, reliable, and secure. The ideal candidate for this role should have a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field, along with at least 3 years of experience in MLOps, data engineering, or a similar role. Proficiency in programming languages such as Python, Spark, and SQL is essential, as well as experience with ML model deployment frameworks and tools like MLflow. Hands-on experience with cloud platforms (AWS, Azure, GCP), containerization (Docker), orchestration tools (Kubernetes), DevOps practices, CI/CD pipelines, and monitoring tools are also required. Key Responsibilities: - Data Engineering and Pipeline Management: Design, develop, optimize, and maintain ETL processes and data pipelines, ensuring data quality, integrity, and consistency. Collaborate with data scientists to make data available in the right format for machine learning. - ML Operations and Deployment: Design and optimize scalable ML deployment pipelines, develop CI/CD pipelines for automated model training and deployment, and implement containerization and orchestration tools for ML workflows. Monitor and troubleshoot model performance in production environments. - Infrastructure Management: Manage cloud infrastructure to support data and ML operations, optimize workflows for large-scale datasets, and set up monitoring tools for infrastructure and application performance. - Collaboration and Best Practices: Work closely with data science, software development, and product teams to optimize model performance, and develop best practices for ML lifecycle management. If you are interested in this exciting opportunity, please share your resume at sunitas@pinnacleinfotech.com. Join us at Pinnacle Infotech and drive swift career growth while working on impactful global projects!,

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Data Engineer