Data & AI Architect

Job Description

Must Have Technical/Functional Skills

● Strong experience in enterprise data architecture, data engineering, BI, and analytics platforms.

● Hands-on experience designing and implementing modern data warehouses, data lakes/lakehouses, and

ETL/ELT pipelines.

● Experience with modern data platforms such as Databricks, SingleStore, Snowflake, Oracle, and/or Vertica.

● Strong knowledge of data integration across cloud platforms, databases, APIs, and enterprise applications.

● Experience with data modeling, data governance, data lineage, data quality, and observability frameworks.

● Strong understanding of ETL/data pipeline management and scripting/automation.

● Experience supporting enterprise reporting, analytics, CRM, AI, and operational platforms.

● Hands-on knowledge of AI model development and integrating AI/ML capabilities with enterprise data platforms.

● Experience with LangChain and/or LlamaIndex for building enterprise AI/GenAI solutions.

● Experience with Vector Databases, including vector search, embeddings, and retrieval-based AI solutions.

● Understanding of RAG (Retrieval-Augmented Generation) architecture and integration of structured and

unstructured enterprise data with AI applications.

● Understanding of cloud architecture, security, resiliency, performance, regulatory compliance, and IT

governance.

● Strong communication and organizational skills with the ability to work with business, architecture, engineering,

and technology teams.

Roles & Responsibilities

● Architect and design scalable enterprise data, BI, analytics, and AI platforms.

● Design and implement modern data warehouses, lakehouse architectures, and scalable ETL/ELT data pipelines.

● Lead data integration initiatives involving cloud platforms, databases, APIs, and enterprise applications.

● Define enterprise data models, architecture standards, and best practices for platforms such as Databricks,

SingleStore, Snowflake, Oracle, and Vertica.

● Establish and enhance data governance, lineage, observability, and data-quality frameworks to create trusted

and reusable enterprise data assets.

● Design data architectures supporting reporting, analytics, CRM, AI/ML, GenAI, and operational use cases.

● Develop and integrate AI-driven solutions using AI models, LangChain/LlamaIndex, vector databases,

embeddings, and RAG architectures.

● Partner with business and technology teams to translate functional requirements into scalable technical and data

solutions.

● Drive cloud and data platform modernization initiatives with a focus on scalability, performance, resiliency,

security, and compliance.

● Provide technical leadership and architectural guidance across data architecture, ETL design, data onboarding,

AI integration, and platform engineering.