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.
Define reusable architecture patterns and ensure solutions align with enterprise architecture and IT governance
standards