Data Engineer Vacancy in Bhubaneswar

Data Engineer Vacancy in Bhubaneswar

Role Overview

The primary objective of this role is to design, architect, and lead the implementation of machine learning and AI solutions.

Key Responsibilities

Demand Generation:

• Assist in the development of solutions to drive demand.
• Support the Go-To-Market strategy.
• Contribute to the creation of solutions and proof of concepts aligned with key offerings to enable solution-led sales.
• Collaborate with various colleges and institutes for research initiatives and the development of data science courses.

Revenue Generation:

• Build and operationalize Machine Learning and Deep Learning solutions.
• Develop machine learning and deep learning models for decision augmentation and automation solutions.
• Work alongside ML Engineers, Data Engineers, and IT teams to assess ML deployment options.

Team Management:

• Manage talent effectively.
• Support onboarding and training to enhance team capability and effectiveness.

Stakeholder Interaction

Stakeholder Types and Interaction Purposes:

Internal Stakeholders:

• Practice Head/Lead: Gather requirements and inputs for devising ML solutions.
• Sales Team, Pre-Sales, Consulting: Aid in defining AI/ML propositions to drive opportunities.
• Talent Transformation Team, Competency Group: Plan and support the delivery of technical training and knowledge sharing.

External Stakeholders:

• Clients: Deliver client projects and establish trust.
• Academia/Colleges/Universities: Collaborate on research initiatives, training programs, and data science courses.

Required Competencies

Functional Competencies/Skills:

• Domain/Industry Knowledge: Basic understanding of industry-specific knowledge relevant to the role.
• Market Intelligence: Foundational understanding of the practice domain, market trends, and competitive landscape.
• Systems Thinking: Ability to understand interdependencies within the Wipro system and solve problems in complex environments.
• Leveraging Technology: Proficient knowledge in technology domains and expert authority in relevant areas.
• Research Orientation: Familiarity with research methods and theoretical concepts to drive experimentation and results.

Competency Levels:

• Foundation: Basic knowledge of competencies with some ability to demonstrate them with minimal support.
• Competent: Consistently demonstrates the full range of competencies independently, even in challenging situations.
• Expert: Applies competencies in all scenarios and guides others.
• Master: Coaches and builds organizational capability in competencies, recognized as a key resource.

Behavioral Competencies:

• Innovation
• Client Centricity
• Execution Excellence
• Passion for Results

Performance Metrics

1. Demand Generation: Number of Proof of Concepts (PoC) supported.
2. Revenue Generation: Timeliness, customer success stories, and customer use cases.
3. Capability Building & Team Management: Number of skills acquired.