Information Technology, AI and Data Sciences

Artificial Intelligence and Data Engineeeing

This role focuses on designing, building, and maintaining systems that process and analyze large datasets to extract insights and power intelligent applications. Professionals in this field are crucial for developing AI models and implementing data-driven solutions.

Career role details and responsibilities

This role focuses on designing, building, and maintaining systems that process and analyze large datasets to extract insights and power intelligent applications. Professionals in this field are crucial for developing AI models and implementing data-driven solutions. Artificial Intelligence and Data Engineeeing sits within the Information Technology, AI and Data Sciences career cluster and focuses on applying domain knowledge to practical problems.

Role details

This role focuses on designing, building, and maintaining systems that process and analyze large datasets to extract insights and power intelligent applications. Professionals in this field are crucial for developing AI models and implementing data-driven solutions. Artificial Intelligence and Data Engineeeing sits within the Information Technology, AI and Data Sciences career cluster and focuses on applying domain knowledge to practical problems.

Responsibilities

Key responsibilities include developing and implementing machine learning algorithms, building data pipelines, ensuring data quality and integrity, and deploying AI models into production environments. They also work on optimizing data storage and retrieval for efficient processing. Typical responsibilities include understanding user or business needs, applying relevant tools and methods, and coordinating with stakeholders.

Next Gen career options

AI Ethics Specialist, AI Product Manager, Machine Learning Operations (MLOps) Engineer, Edge AI Developer, AI Governance Specialist, Quantum Machine Learning Researcher.

Pointer: Next Gen career options related to this role

AI Ethics Specialist, AI Product Manager, Machine Learning Operations (MLOps) Engineer, Edge AI Developer, AI Governance Specialist, Quantum Machine Learning Researcher.

Educational institutes

Top 5 educational institutes in India

Name of Institute Location Website
Indian Institute of Technology Bombay Mumbai, Maharashtra https://www.iitb.ac.in/
Indian Institute of Technology Delhi New Delhi, Delhi https://home.iitd.ac.in/
Indian Institute of Science Bengaluru, Karnataka https://www.iisc.ac.in/
National Institute of Technology Trichy Tiruchirappalli, Tamil Nadu https://www.nitt.edu/
Jawaharlal Nehru Centre for Advanced Scientific Research Bengaluru, Karnataka https://www.jncasr.ac.in/

Top 5 educational institutes globally

Name of Institute Location Website
Massachusetts Institute of Technology (MIT) Cambridge, USA https://www.mit.edu/
Stanford University Stanford, USA https://www.stanford.edu/
Carnegie Mellon University Pittsburgh, USA https://www.cmu.edu/
University of Oxford Oxford, UK https://www.ox.ac.uk/
University of Toronto Toronto, Canada https://www.utoronto.ca/
Refer our tool Unifinder to explore university matching your requirements https://counselnavi.com/uni-finder
Career role Name
Artificial Intelligence and Data Engineeeing
Career Cluster
1.2 Information Technology, AI and Data Sciences
Super Cluster
1. Technology, Engineering & Digital Systems
Industry alignment
Technology (Software Development, Cloud Computing, Cybersecurity), Finance (Algorithmic Trading, Risk Management), Healthcare (Diagnostics, Drug Discovery), E-commerce (Recommendation Systems, Personalization), Automotive (Autonomous Driving).
Work environment
Typically an indoor, office-based environment with standard working hours (9 AM to 5 PM). Many roles offer hybrid or remote work options, promoting a good work-life balance. Collaboration with cross-functional teams is common.
Opportunity Type
High growth potential due to increasing demand for data-driven insights and AI capabilities. Offers significant opportunities for creativity in problem-solving and innovation. Salary growth is robust. The role is generally stable with increasing automation.
Key skills needed
Proficiency in programming languages like Python, R, and Java (Advanced). Strong understanding of machine learning algorithms, statistical modeling, and data structures (Advanced). Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, GCP) (Intermediate to Advanced). Problem-solving and analytical skills (Advanced).
Interest type alignment
Investigative (Analyzing data, understanding patterns), Realistic (Building and implementing systems), Conventional (Organizing and managing data). Aptitudes for logical reasoning, mathematics, and computational thinking are essential.
Career growth Path
0-3 Years: Junior Data Scientist/AI Engineer, Data Analyst. 3-7 Years: Data Scientist, AI Engineer, Machine Learning Engineer. 7-12 Years: Senior Data Scientist, Lead AI Engineer, AI Architect. 12+ Years: Head of Data Science, Chief AI Officer, Principal Data Architect.
Suggested education Pathways 10th standard onwards
1. Bachelor's in Computer Science/Engineering followed by Master's in Data Science or AI. 2. Bachelor's in Statistics/Mathematics followed by specialized courses or Master's in Data Science. 3. Integrated Master's programs in Data Science or AI.
Education Stream recommendations
Technology, Engineering & Digital Systems
Demand in India
High demand across major tech hubs like Bangalore, Hyderabad, Pune, and Delhi NCR. Companies are actively seeking professionals for roles in analytics, AI development, and machine learning.
Demand globally
Very high demand globally, with significant opportunities in North America, Europe, and parts of Asia. The growth of AI and big data across industries fuels this demand.
Career & Job Prospects
Diverse job opportunities exist, including Data Scientist, Machine Learning Engineer, AI Engineer, Data Analyst, Business Intelligence Analyst, and AI Researcher. Related role families include Software Development and IT Services.