Enterprise Data & AI Architect

Ztek Consulting; Jersey City (NJ); On-site; USD 140,000 - 190,000; Full time

Job summary

Ztek Consulting, Inc. is seeking an experienced Senior Data Architect to design scalable enterprise data, BI, and AI platforms onsite in Jersey City, NJ or Plano, TX. You will lead data modeling, governance, and modern data warehouse/lakehouse initiatives across cloud environments.

Work with business, architecture, and engineering teams to translate requirements into robust data solutions, mentor engineers, and advance AI/GenAI integrations using LangChain, LlamaIndex, and vector databases.

Qualifications

• Experience in enterprise data architecture, data modeling, governance, and observability.
• Hands-on design and implementation of data warehouses/lakehouses and data pipelines.
• Familiarity with Databricks, Snowflake, Oracle, and Vertica platforms; integration across cloud providers.

Responsibilities

• Lead the design of scalable enterprise data, BI, analytics, and AI platforms.
• Architect and implement modern data warehouses and lakehouse architectures.
• Oversee ETL/ELT pipelines and data integration across cloud, databases, and APIs.
• Drive data governance, lineage, and quality frameworks across the enterprise.
• Collaborate with business, architecture, and engineering teams to translate requirements into scalable solutions.
• Guide AI/GenAI integrations using LangChain/LlamaIndex and vector databases.
• Provide technical leadership and set architecture standards for data platforms.

Skills

Enterprise data architecture

Data engineering

BI & analytics platforms

AI/GenAI integration

Cloud platform experience

Communication & collaboration

Tools

Databricks

SingleStore

Snowflake

Oracle

Vertica

LangChain

LlamaIndex

Vector databases

Job description

Location : Jersey City, NJ or Plano, TX - Onsite

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

• 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.

• 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