Lead Engineer - Data Scientist @ Advance Immigrations

Job Description

Professional | Full-Time | Engineering Vestas is the world leader in wind technology and a driving force in the development of the wind power industry. Vestas core business comprises the development, manufacture, sale, marketing and maintenance of Wind Turbines. Come and join us at Vestas! Applications, Controls & Electrical > Modelling & Analytics Module > Plant Monitoring & Reliability Plant Monitoring & Reliability Sub Module, within the Modelling & Analytics Module, Part of Vestas Power Solutions, is responsible for the products and services related to Vestas Monitoring and Reliability solutions and offerings. We have a solid and diverse team with a global presence, that consists of highly skilled Health/Condition Monitoring & Reliability Engineers/Specialists, Statisticians, Data engineers & Data Scientists. The department is responsible for developing world-class Plant Monitoring Products & Solutions that include Health/Condition Monitoring, Power Quality Monitoring. Reliability, Failure Predictors & CMS data Products. This is enabled through real-time data collection from thousands of power plants with CMS systems, IoTs on Health Monitoring & Reliability setup supporting multiple data applications, data products, diagnostics, and monitoring solutions for our internal & external customers. The end goal is to bring down the cost of energy by leveraging the vast amount of data that Vestas collects and stores from power plants around the globe. The team is characterized by Vestas values: Accountability, Collaboration, Simplicity, and Passion which form the backbone for our culture of striving for world-class. Vestas M&A is on a journey of transitioning into a Cloud-based data platform for Plant & Reliability data. You will be the core Senior Data Analyst, responsible for the development and implementation of this transition, and become part of the design of modern data product offerings for the Reliability area. The primary scope of work will be sourcing data from distributed on-premise data systems to develop and predict product performance through data science methodologies. Responsibilities Work with large data sets to solve complicated data analysis problems using statistical and machine-learning approaches Design and implement able-to-scale mathematical & predictive models, classifiers leveraging machine learning, data regression Development of API, Kubernetes, and integration of different modules in the Cloud Azure environment Manage & Coordinate with a test data architecture for selecting the platform and developing the application to finally testing and implementing a solution Design and support database and table schemas for new and existent data sources, proof of concepts, algorithms, and custom analysis Translate business needs into technical data designs Design and implement implementation of ETL (Extract, Transform, Load) data pipelines Qualifications Bachelor's / Master's in any engineering specialization Minimum of 5-7 years of Relevant experience within STEM (Science, Technology, Engineering, and Mathematics) Work experience where data science, data engineering, and application development wereThe a major part of your work in automating software deployments and following a continuous delivery and deployment model Experience with mathematical & statistical modeling, Cloud environment, APIs, Kubernetes Solid experience in program coding with Python, SQL, .NET, C# or R Competencies Must have Python, Snowflake, Snowpark, Unity Catalog, Azure cloud & DevOps, SQL, CI/CD, Cloud infrastructure deployment Good to have: Databricks, Spark, Pandas, Data Factory, Data/Delta Lake, git, testing To build database-powered applications, data models, and proficiency with ETL tools, MS SQL, SSIS, SSAS (MDX/DAX) JIRA or similar tools Experience with Cloud platform (SNOWFLAKE) & Knowledge of Kafka, C#, Kubernetes Experience in data science, machine learning or artificial intelligence technologies What We Offer We offer you the opportunity to make a difference and to work in a multicultural and international company, where you have the possibility to improve your skills and develop professionally. Additional Information Your primary workplace will be in Chennai, India. Please note: We do amend or withdraw our jobs and reserve the right to do so at any time, including prior to the advertised closing date. Please be advised to apply on or before 21st March 2024. About Vestas Vestas is the energy industrys global partner on sustainable energy solutions. We are specialised in designing, manufacturing, installing, and servicing wind turbines, both onshore and offshore. Across the globe, we have installed more wind power than anyone else. We consider ourselves pioneers within the industry, as we continuously aim to design new solutions and technologies to create a more sustainable future for all of us. With more than 145 GW of wind power installed worldwide and 40+ years of experience in wind energy, we have an unmatched track record demonstrating our expertise within the field. With 29,000 employees globally, we are a diverse team united by a common goal: to power the solution today, tomorrow, and far into the future. Vestas promotes a diverse workforce which embraces all social identities and is free of any discrimination. We commit to create and sustain an environment that acknowledges and harvests different experiences, skills, and perspectives. We also aim to give everyone equal access to opportunity. To learn more about our company and life at Vestas, we invite you to visit our website at www.vestas.com and follow us on our social media channels. We also encourage you to join our Talent Universe to receive notifications on new and relevant postings

Employement Category:

Employement Type: Full time
Industry: Power / Energy
Role Category: Statistics / Analytics
Functional Area: Not Applicable
Role/Responsibilies: Lead Engineer - Data Scientist

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Keyskills:   Python SQL NET C R Snowflake DevOps Kubernetes Spark git MS SQL SSIS SSAS JIRA Kafka Data science Machine learning Artificial intelligence Snowpark Unity Catalog Azure cloud CICD Databricks Pandas Data Factory DataDelta Lake MDXDAX