Data & AI Architect

Centraprise; Jersey City (NJ); Vor Ort; USD 120.000 - 190.000; Vollzeit

Zusammenfassung

Centraprise, Corp. in New Jersey seeks an experienced Enterprise Data Architect to lead scalable data platforms for analytics, including data warehouses and lakehouses.

You will drive ETL/ELT pipelines, data governance, lineage, and cross‑cloud data integration, partnering with business, architecture, and engineering teams.

The role emphasizes hands-on leadership in modern data stacks and AI integration with a focus on security, resiliency, and compliance.

Qualifikationen

• Must have extensive experience building and operating enterprise data architectures.
• Expertise in designing scalable data warehouses, lakehouses, and analytics platforms.
• Strong knowledge of cloud data platforms and data integration across multiple environments.
• Proven ability to implement data governance, lineage, quality, and observability frameworks.
• Hands-on ETL/ELT development and automation across complex data landscapes.
• Experience with AI/GenAI integrations and enterprise data strategies.

Kenntnisse

Data architecture

Data engineering

Data warehouses

Data lakes

Databricks

Snowflake

Data governance

ETL pipelines

AI integration

GenAI

LangChain

LlamaIndex

Vector databases

Jobbeschreibung

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, resilience,
• 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