Data and integration consultant

About Us

Tata AutoComp Systems has embarked on the Digital Transformation journey for the entire organisation from shopfloor to enterprise.

The Data & AI Integration Lead will play a critical role in delivering enterprise‑wide Data, Analytics, and AI capabilities, acting as both a tactical leader and hands‑on technical authority. The role requires deep expertise in AI/ML solution delivery, Databricks‑based platforms, cloud technologies, and AI lifecycle management, with a strong focus on scalable architectures, cost efficiency, and measurable business impact.

Key Responsibilities

• Understanding of applicability of AI in context of  Manufacturing industry and applicable digital technologies like MES, EMS, Immersive etc.
• Execute the Data & AI roadmap aligned with Industry 4.0 and business objectives
• Architect scalable, secure Data and AI platforms using Databricks, cloud-native services, and modern data architectures
• Lead end‑to‑end AI solution delivery, from data ingestion and feature engineering to model deployment, monitoring, and optimization
• Establish and operationalize an AI Factory model, governing the complete AI lifecycle across use cases and business units
• Design and implement AI and analytics solutions using Python, covering time‑series forecasting, optimization, predictive analytics, and classification/regression problems
• Apply deep learning techniques (CNN, RNN, LSTM) and leverage Generative AI where applicable (RAG architectures, prompt engineering, LLM evaluation), Agentic Orchestration & Pipeline Development
• Lead deployment of AI solutions on cloud platforms (AWS preferred; Azure/GCP exposure) using containerization, Kubernetes, and CI/CD pipelines
• Drive Agile / SCRUM execution, managing multiple workstreams and enabling cross‑functional collaboration
• Communicate AI outcomes, risks, and value realization clearly to senior business and technology leadership

Qualification

BE / BTech in Computer Science & Engineering, Information Technology, AI/ML, Electronics & Communication, Electrical Engineering

Experience

8-12 Years

Additional Requirement

AI & Data Platform Expertise

AI Lifecycle & MLOps

Cloud & Architecture

Cost Management & FinOps

AI Strategy, Governance & Leadership

Behavioural Skills

Competencies