Senior Solution Architect

As a Data & AI Solution Architect, you will design and drive enterprise-scale data, analytics, and AI solutions across cloud platforms. You will partner with business and tech stakeholders to create scalable, secure architectures and modern data platforms, enabling AI-driven capabilities that deliver measurable value. You’ll provide technical leadership for data and AI initiatives, mentoring teams and shaping the organization’s data/AI strategy. This role blends strategic thinking with hands-on engineering, communicating complex concepts to executives. A compelling hook is shaping lakehouse-based architectures and GenAI-enabled solutions at scale.

• Define and lead architecture, design, and implementation of enterprise-scale Data & AI solutions on cloud platforms (Azure, AWS, GCP).
• Design modern data platforms using Databricks, Snowflake, data lakes, lakehouses, and cloud-native analytics services.
• Collaborate with stakeholders to translate requirements into scalable, secure architectures.
• Lead development of Generative AI, LLM-powered apps, AI agents, and RAG-based solutions for business challenges.
• Evaluate vector databases, agent frameworks, and AI orchestration platforms to support advanced use cases.
• Set data modelling standards and guide conceptual, logical, and physical data design.
• Define data integration strategies and oversee ETL/ELT pipelines with modern frameworks/tools.
• Ensure solutions comply with governance, security, privacy, compliance, and risk management standards.
• Provide technical leadership, architecture governance, and design reviews across initiatives.
• Collaborate with engineering, platform, and operations teams for delivery and adoption.
• Drive innovation by evaluating emerging tech and best practices in Data, Analytics, AI, and Agentic AI.
• Mentor architects and engineers, fostering engineering excellence and continuous learning.
• Support presales, solution proposals, estimations, and technical discussions with customers/partners.
• Present architecture recommendations and transformation roadmaps to senior leadership.

• 14+ years of experience in data architecture, data engineering, or related roles
• 8+ years hands-on with cloud data platforms (AWS, Azure, and/or GCP) in architecture, design, and implementation
• Hands-on with Databricks and/or Snowflake for large-scale data engineering and lakehouse workloads
• Hands-on experience with AI/ML solutions, including LLM-based apps and AI agent design
• Strong data modelling (conceptual/logical/physical), data warehousing, and lakehouse architectures
• Experience with data integration tools/ETL-ELT frameworks (Informatica, dbt, Talend, Glue, ADF)
• Knowledge of vector databases (e.g., Pinecone, FAISS, pgvector) and RAG architectures
• Experience with agent frameworks/protocols (e.g., LangChain, LangGraph, AutoGen, MCP) desirable
• SQL proficiency and Python for prototyping/integration
• Understanding of data governance, security, privacy/compliance (e.g., GDPR)
• Strong stakeholder management, communication, and technical leadership

• stakeholder management
• clear communication
• leadership and mentoring
• Databricks
• Snowflake
• Azure