Engineering Lead – Data, AI & Digital Manufacturing

Tata Electronics; India; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Tata Electronics seeks an Engineering Lead for Data, AI & Digital Manufacturing to design, build, and lead scalable platforms powering smart semiconductor fabrication. You will drive data ingestion, AI deployment, and cross-functional collaboration to transform fab operations.

The role requires strong hands-on experience with data platforms, cloud solutions, and leadership in manufacturing settings, enabling AI-driven decisions and operational excellence.

Qualifications

• Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, or related field.
• Strong experience in Manufacturing domains.
• Proven hands-on experience with AI/ML systems in industrial or manufacturing environments.
• Deep expertise in data ingestion, transformation, and orchestration pipelines.
• Experience working with both structured and unstructured data at scale.
• Hands-on experience with Databricks, Snowflake, or hyperscalers data warehouse platforms.
• Strong experience with cloud platforms
• Experience integrating OT, IoT, and enterprise systems in manufacturing environments.
• Strong programming skills in Python, SQL, and data engineering frameworks.
• Experience leading and mentoring engineering teams is highly desirable.

Responsibilities

• Lead engineering teams delivering data platforms and AI solutions for manufacturing.
• Design and implement end-to-end data ingestion, transformation, and processing pipelines for high-volume, high-velocity manufacturing data.
• Integrate OT systems (equipment, MES), IoT platforms, and enterprise systems (ERP, PLM, quality systems).
• Architect and manage platforms handling structured and unstructured data, including sensor data, images, logs, and time-series data.
• Develop and deploy AI/ML solutions for yield improvement, predictive maintenance, quality analytics, and operational optimization.
• Leverage cloud platforms to build scalable, secure, and resilient data and AI platforms.
• Drive adoption of Databricks, Snowflake, or hyperscalers data platforms within manufacturing ecosystems.
• Collaborate closely with fabrication, manufacturing, quality, IT, and business teams to translate operational needs into technical solutions.
• Establish engineering best practices for data governance, security, reliability, and scalability.
• Mentor engineers, conduct code and architecture reviews, and build a strong data and AI engineering culture.

Skills

Python

SQL

Data engineering

AI/ML

Cloud platforms

Databricks

Snowflake

Leadership

Education

Bachelor's or Master's in Engineering/CS/Data Science

Tools

Databricks

Snowflake

Job description

About Tata ElectronicsTata Electronics Private Limited (TEPL), a wholly owned subsidiary of Tata Sons Pvt. Ltd., is a greenfield venture of the Tata Group focused on manufacturing precision components and building India’s first AI-enabled, state-of-the-art Semiconductor Foundry. The foundry will manufacture chips for power management ICs, display drivers, microcontrollers (MCUs), and high-performance computing logic, serving markets such as automotive, computing and data storage, wireless communications, and artificial intelligence. Guided by the Tata Group’s mission to improve quality of life through leadership with trust, TEPL is shaping India’s semiconductor future.

Role Overview

The Engineering Lead – Data, AI & Digital Manufacturing will play a critical role in designing, building, and leading scalable data and AI platforms that power smart semiconductor manufacturing. This role will drive integration across OT, IoT, and enterprise systems, enabling advanced analytics, AI-driven decision-making, and digital transformation across fab operations.

Key Responsibilities

• Lead engineering teams delivering data platforms and AI solutions for manufacturing.
• Design and implement end-to-end data ingestion, transformation, and processing pipelines for high-volume, high-velocity manufacturing data.
• Integrate OT systems (equipment, MES), IoT platforms, and enterprise systems (ERP, PLM, quality systems).
• Architect and manage platforms handling structured and unstructured data, including sensor data, images, logs, and time-series data.
• Develop and deploy AI/ML solutions for yield improvement, predictive maintenance, quality analytics, and operational optimization.
• Leverage cloud platforms to build scalable, secure, and resilient data and AI platforms.
• Drive adoption of Databricks, Snowflake, or hyperscalers data platforms within manufacturing ecosystems.
• Collaborate closely with fabrication, manufacturing, quality, IT, and business teams to translate operational needs into technical solutions.
• Establish engineering best practices for data governance, security, reliability, and scalability.
• Mentor engineers, conduct code and architecture reviews, and build a strong data and AI engineering culture.

Required Qualifications & Experience

Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, or related field. Strong experience in Manufacturing domains. Proven hands-on experience with AI/ML systems in industrial or manufacturing environments. Deep expertise in data ingestion, transformation, and orchestration pipelines. Experience working with both structured and unstructured data at scale. Hands-on experience with Databricks, Snowflake, or hyperscalers data warehouse platforms. Strong experience with cloud platforms Experience integrating OT, IoT, and enterprise systems in manufacturing environments. Strong programming skills in Python, SQL, and data engineering frameworks. Experience leading and mentoring engineering teams is highly desirable.

Preferred Skills

Experience with semiconductor fab systems such as MES, equipment interfaces, and yield management systems. Exposure to real-time streaming platforms and time-series databases. Understanding of data governance, cybersecurity, and compliance in manufacturing environments. Strong stakeholder management and cross-functional collaboration skills. Ability to work in fast-paced, greenfield environments and build platforms from scratch.