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Enterprise Architect

Alltech Consulting Services, Inc.Scottsdale, AZ🇺🇸United StatesPosted Oct 1, 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Scottsdale, AZ, United States
Posted
23 hours ago
DockerMicroservicesOracleSQLSQL ServerAWSETLMLOpsMachine LearningSnowflakeApacheApache SparkAzureCloudFormationDatabricksGenerative AIGoogle CloudGraphQLHadoopHiveJenkinsKafkaKubernetesLLMPostgreSQLRESTStakeholder ManagementTerraform

Job Description

Role : Enterprise Architect

Location : Scottsdale AZ (Onsite)

Fulltime role

Must have :

core skills - Databricks, Cloudera, Snowflake, Data engineering

Role Overview

We are seeking a highly experienced Enterprise Architect to define and drive the enterprisetechnology 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/Google Cloud Platform), 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 Google Cloud Platform.
  • 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.

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 (Google Cloud Platform)
  • 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.

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