Full Stack Developer

1 month ago

Kolkata, India Sibia analytics Full time
Description

:· Experience with Additional Front-end Frameworks: Knowledge of additional front-end frameworks beyond the core ones, such as Ember.js, Backbone.js, or Knockout.js, can be advantageous.· Mobile Development: Familiarity with mobile application development using frameworks like React Native, Flutter, or Ionic can be beneficial, as it allows for building cross-platform mobile apps.· Cloud Computing: Experience with cloud platforms like AWS (Amazon Web Services), Azure, or Google Cloud Platform, and knowledge of deploying and scaling applications using cloud services such as EC2, S3, or Lambda.· DevOps and Deployment: Proficiency in CI/CD (Continuous Integration/Continuous Deployment) practices and tools like Jenkins, Travis CI, or CircleCI, as well as experience with containerization technologies like Docker and orchestration tools like Kubernetes.· Knowledge of Backend Languages: Familiarity with additional backend languages like Java, C#, or Go, and frameworks such as Spring, .NET, or Gin, can broaden your development opportunities.· Security Awareness: Understanding of web application security principles and best practices, including common vulnerabilities and mitigation strategies, such as OWASP Top 10.

Requirements

:· Define processes for creating data engineering solutions and use advanced technologies to support Adani AI Labs Data Scientist Team

· Mentor Data Engineering Team to address data engineering solution requirements

· Track industry trend, drive data standards and best practices, and leverage latest industry technologies to increase efficiency of Data Engineering prototypes

Ensure that AI solutions create measurable business value (aligned with business objectives of asset utilization,employee engagement, customer · engagement, and business modelling) and generate actionable business insights

· Collaborate with the solution management, data engineering, ML engineering and AI Architect teams to create and drive the technical solution roadmap

· Drive the data engineering practice by setting SMART goals and drive delivery of the data engineering component of AI solutions and implementation of technical solutions

· Actively identify and resolve strategic data issues that may impair the team’s ability to meet strategic, scientific, and technical goals

· Present the results of data engineering prototypes before non-technical members (e.g., Business Teams) of the organization through presentations and immersive storytelling· Collaborate with AI Solution Manager to allocate data engineering resources for different AI Solution projects

· Collaborate with Business Data Analyst, AI Champion and Solution Managers to define business requirements and fulfil solution data requirements

· Collaborate with Data Engineer, ML Engineers, AI Architects and Solution Managers to create Data engineering solutions• Build Capacity and capability for the Data Engineering function

• Nurture a high-performance culture

• Create a highly engaged and agile team to tackle AI solution projectsBenefits

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