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 contemporary 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

📌 Data Architecture & AI (Delhi)
🏢 Symbiosis Management Consultants P
📍 Delhi