Enterprise Architect

Job Description

Job Description

Role : Enterprise Architect

Location : Scottsdale AZ (Onsite)

Salary : $140K

Must have :

core skills - Databricks, Cloudera, Snowflake, Data engineering

Role Overview

We are seeking a highly experienced Enterprise Architect to define and drive the enterprise technology strategy across Data Platforms, Cloud, AI/ML, Analytics, and Enterprise Integration. The ideal candidate will be responsible for designing scalable, secure, and future-ready architectures leveraging Databricks, Snowflake, Hadoop, Cloud Platforms (AWS/Azure/GCP), APIs, Data Engineering, Automation, and AI/ML technologies.

The architect will collaborate with executive leadership, business stakeholders, engineering teams, and customers to build enterprise-scale digital, data, and AI solutions that maximize business value and operational efficiency.

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Key Responsibilities

Enterprise Architecture & Strategy

• Define enterprise-wide architecture standards, reference architectures, and technology roadmaps.

• Lead architecture governance, solution reviews, and technology selection decisions.

• Design scalable, resilient, secure, and cost-optimized enterprise platforms.

• Align technology architecture with business objectives and digital transformation initiatives.

• Drive cloud adoption, modernization, and platform engineering programs.

Data Platform Architecture

• Architect enterprise data platforms using Databricks, Snowflake, Hadoop, and cloud-native services.

• Design modern Lakehouse, Data Warehouse, and Data Mesh architectures.

• Define enterprise data governance, metadata management, lineage, and security frameworks.

• Establish data quality, observability, monitoring, and compliance standards.

• Design structured and unstructured data management strategies.

Data Engineering & ETL

• Architect large-scale ETL/ELT frameworks for batch and real-time processing.

• Lead the design of scalable data pipelines across multiple source systems.

• Define data integration patterns using Spark, Databricks, Hadoop ecosystem, and cloud-native services.

• Establish best practices for ingestion, transformation, orchestration, and data delivery.

• Optimize performance and scalability of enterprise data pipelines.

Cloud Architecture

• Design enterprise solutions across AWS, Azure, and GCP.

• Drive cloud migration and modernization initiatives.

• Architect highly available, secure, and scalable cloud platforms.

• Define Infrastructure as Code (IaC), CI/CD, and DevOps strategies.

• Ensure cloud governance, security, networking, and FinOps best practices.

AI/ML & Advanced Analytics

• Define enterprise AI/ML architecture strategy.

• Architect MLOps frameworks and model lifecycle management.

• Design Generative AI, Agentic AI, RAG, and LLM integration architectures.

• Establish AI governance, monitoring, security, and responsible AI practices.

• Enable business intelligence, predictive analytics, and advanced AI capabilities.

API & Integration Architecture

• Define enterprise integration architecture and API strategy.

• Design microservices, event-driven, and API-first architectures.

• Establish integration patterns using REST APIs, GraphQL, messaging systems, and streaming frameworks.

• Ensure secure, scalable, and reusable enterprise integrations.

Quality Engineering & Test Automation

• Define enterprise testing strategy for data, cloud, APIs, and applications.

• Architect automated testing frameworks for ETL, Data Quality, API, AI/ML, and cloud platforms.

• Drive adoption of CI/CD-integrated quality engineering practices.

• Establish reliability, observability, and performance testing standards.

Leadership & Stakeholder Management

• Act as trusted advisor to business and technology leadership.

• Mentor architects, engineers, and technical leads.

• Lead architecture reviews and technical governance forums.

• Drive innovation and adoption of emerging technologies.

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Required Technical Skills

Data Platforms

• Databricks Lakehouse

• Snowflake

• Hadoop Ecosystem (HDFS, Hive, Spark, YARN)

• Data Warehouse & Data Lake Platforms

• Delta Lake

• Data Mesh & Data Fabric

Data Engineering

• ETL / ELT Architecture

• Data Pipelines

• Apache Spark

• PySpark

• Kafka

• Streaming & Real-Time Processing

• Data Quality & Observability

Cloud Platforms

• AWS

• Microsoft Azure

• Google Cloud Platform (GCP)

• Cloud Security & Networking

• Infrastructure as Code (Terraform, CloudFormation)

AI/ML

• Machine Learning Platforms

• MLOps

• Generative AI

• Large Language Models (LLMs)

• Agentic AI

• RAG Architectures

• Vector Databases

API & Integration

• REST APIs

• GraphQL

• Enterprise Service Bus (ESB)

• Event-Driven Architecture

• Microservices

Automation & DevOps

• CI/CD Pipelines

• GitHub/GitLab

• Jenkins

• Docker

• Kubernetes

• Test Automation Frameworks

Database Technologies

• Snowflake

• SQL Server

• PostgreSQL

• Oracle

• NoSQL Databases

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Soft Skills

• Executive stakeholder management

• Strategic thinking

• Architectural leadership

• Strong communication and presentation skills

• Problem-solving and decision-making

• Customer engagement and consulting experience

This Enterprise Architect role is ideal for organizations looking to build and modernize enterprise-scale Data, AI, Cloud, and Digital platforms while driving innovation, governance, and business transformation.