Data Architecture & AI

Purpose of the Role

Own and drive the enterprise data & AI strategy

Design and implement scalable data architecture (data lake, warehouse,

pipelines)

Lead adoption of Analytics, ML, and GenAI to unlock business value

• Act as a bridge between business, IT, and advanced analytics teams

Key Responsibilities

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