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 contemporary 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.

Requisites
- 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.

📌 Lead Data Engineering & AI (India)
🏢 MASTER MIND CONSULTANCY
📍 India