Lead Data Architect

Kajaria Ceramics; Delhi; On-site; INR 2,000,000 - 5,200,000; Full time

Job summary

Kajaria Ceramics in Delhi seeks a Lead Data Architecture & AI to own the enterprise data & AI strategy, designing scalable data architecture (data lake, data warehouse, pipelines) and driving analytics, ML, and GenAI adoption to unlock business value. The role bridges business, IT, and analytics teams.

The candidate will lead data governance, platform build, and governance while mentoring data engineers and scientists to deliver measurable outcomes.

Qualifications

• 8–10 years of experience in data engineering, analytics, or AI/ML
• Build enterprise-scale data platforms with governance and security
• Ability to translate business problems into data & AI solutions

Responsibilities

• Own data architecture and platform build (data lake/warehouse/lakehouse)
• Lead analytics, BI, and self-service data initiatives
• Drive AI/ML and GenAI use cases with responsible AI governance
• Establish data governance, catalog, lineage, and MDM practices
• Lead cross-functional teams and manage vendors/partners

Skills

Data platforms

ETL/ELT pipelines

BI tools

ML frameworks

GenAI exposure

Analytics use cases

Strategic translation of business

Education

Bachelor’s/Master’s in Engg/CS/DS

Tools

Snowflake

Databricks

Azure/AWS data stack

Power BI

Tableau

Python

TensorFlow/PyTorch

Job description

JOB DESCRIPTION

Role Title

Lead Data Architecture & AI

Role Summary

The role is responsible for owning and driving the enterprise data & AI strategy, designing and implementing scalable data architecture (data lake, data warehouse, pipelines), and leading the adoption of Analytics, ML, and GenAI to unlock business value. The role will also act as a bridge between business, IT, and advanced analytics teams.

Key Responsibilities

1. Data Architecture & Platform Build

• Design and implement modern data architecture (Data Lake, Data Warehouse, Lakehouse)
• Define data models, standards, governance, and security frameworks
• Build scalable data pipelines (batch + real-time ingestion)
• Ensure high availability, performance, and cost optimization of data platforms

2. Analytics & Visualization

• Enable self-service analytics and reporting platforms
• Lead implementation of BI tools and dashboards
• Partner with business teams to define KPIs, metrics, and insights frameworks
• Drive adoption of data-driven decision making

3. AI / ML / GenAI Initiatives

• Identify and deliver high-impact AI/ML use cases (forecasting, recommendations, optimization)
• Lead development and deployment of machine learning models
• Drive adoption of Generative AI use cases (automation, copilots, knowledge assistants)
• Ensure responsible AI practices including model governance and explainability

4. Data Governance & Quality

• Establish data governance framework (catalog, lineage, ownership)
• Ensure data quality, consistency, and compliance
• Implement master data management (MDM) practices

5. Stakeholder & Program Leadership

• Work closely with business leaders to translate requirements into data solutions
• Lead cross-functional teams (data engineers, analysts, data scientists)
• Manage vendors, partners, and external technology providers
• Drive roadmap execution aligned to business priorities

Key Skills & Expertise

Technical

• Strong experience in Data Platforms (e.g., Snowflake, Databricks, Azure/AWS data stack)
• Expertise in ETL/ELT tools, data pipelines, and data modeling
• Hands-on with BI tools (Power BI, Tableau, etc.)
• Experience in ML frameworks (Python, TensorFlow, PyTorch, etc.)
• Exposure to GenAI / LLM ecosystems

Functional

• Strong understanding of analytics use cases across sales, marketing, supply chain, finance
• Ability to translate business problems into data & AI solutions

Leadership

• Experience in leading data & AI teams or large programs
• Strong stakeholder management and communication skills
• Ability to operate in both strategic and hands-on roles

Experience & Qualifications

• 8–10 years of experience in data engineering, analytics, or AI/ML
• Bachelor’s/Master’s in Engineering, Computer Science, Data Science, or related field
• Experience in building enterprise-scale data platforms
• Prior experience in AI/ML or GenAI initiatives is preferred