Posted 13 August, 2026

Lead Data Engineering & AI

MASTER MIND CONSULTANCY

Mumbai, MH, MH, IN Full Time

Job Title : Lead Data Engineering & AI

Experience : 10 to 15 Years

Location : Mumbai

Roles & Responsibilities

Lead the architecture, design, and implementation of enterprise-scale data platforms, including data warehousing, analytics, reporting, and data distribution.
Design and implement AI/GenAI-powered data solutions using LLMs, RAG architectures, and modern AI/ML technologies.
Build natural language interfaces, conversational AI, and enterprise search capabilities over structured and unstructured data.
Develop and manage AI orchestration frameworks, prompt engineering, retrieval pipelines, and agent-based AI solutions.
Establish AI evaluation frameworks to measure performance, accuracy, security, explainability, and business outcomes.
Ensure AI governance, security, data privacy, auditability, and responsible AI practices across enterprise solutions.
Lead and mentor data engineering teams while promoting innovation, collaboration, and engineering excellence.
Collaborate with business stakeholders, architects, and cross-functional teams to define and execute data and AI strategies.
Drive automation, data quality, observability, CI/CD, Agile delivery, and engineering best practices.
Manage stakeholder communication, project delivery, risks, dependencies, and continuous technology innovation.

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
Strong expertise in Data Engineering, Data Architecture, SQL, ETL, Data Modeling, and scalable data pipelines.
Hands-on experience with cloud data platforms, preferably Snowflake.
Strong domain knowledge of Finance, Investment Banking, or Financial Services.
Experience with AI/GenAI technologies, including LLMs, RAG, Prompt Engineering, Model Orchestration, and AI-driven analytics.
Experience building AI-powered enterprise search, conversational AI, and natural language data interaction solutions.
Strong understanding of AI governance, security, model risk, data privacy, and responsible AI practices.
Experience with SDLC, Agile methodologies, CI/CD, automated testing, and production release management.
Strong leadership, stakeholder management, communication, analytical, and problem-solving skills.
Good knowledge of Python, Shell Scripting, Apache Airflow, Power BI, Vector Search, Embeddings, Agentic AI, Workflow Automation, and AI engineering frameworks.