Enterprise Architect - Data, Cloud & AI

Requirements:

• Strong hands-on enterprise architecture experience across data platforms, cloud, AI/ML, analytics, and enterprise integration.
• Experience with Databricks, Cloudera, Snowflake, Hadoop, data engineering, and cloud platforms.
• Proficiency with data architecture and engineering technologies, including Lakehouse, data lakes and warehouses, Delta Lake, Spark/PySpark, Kafka, ETL/ELT, batch and streaming processing, and data quality and observability.
• Experience with AWS, Microsoft Azure, and Google Cloud Platform, including cloud security, networking, migration, and Infrastructure as Code tools such as Terraform or CloudFormation.
• Knowledge of machine learning platforms, MLOps, generative and agentic AI, LLMs, RAG, vector databases, and AI governance.
• Experience with API and integration technologies, including REST, GraphQL, ESB, event-driven architecture, microservices, messaging, streaming, and API management.
• Familiarity with CI/CD, DevOps, GitHub or GitLab, Jenkins, Docker, Kubernetes, infrastructure automation, and test automation frameworks.
• Knowledge of SQL Server, PostgreSQL, Oracle, NoSQL databases, and enterprise data warehousing.
• Experience leading enterprise data modernization and cloud transformation, designing large-scale data platforms, and working with distributed systems, high-volume processing, and real-time streaming.
• Background in enterprise architecture frameworks, governance models, and technology roadmaps; consulting or customer-facing architecture experience is highly desirable.
• Strong executive stakeholder management, strategic thinking, communication, presentation, consulting, problem-solving, decision-making, leadership, collaboration, and mentoring skills; ability to influence business and technology teams.

Responsibilities:

• Define enterprise architecture standards, reference architectures, technology principles, and strategic roadmaps; lead governance, solution reviews, and technology evaluations.
• Design secure, scalable, resilient, highly available, and cost-effective enterprise platforms aligned with business goals; advance cloud adoption, modernization, platform engineering, and transformation initiatives.
• Architect data platforms and Lakehouse, warehouse, lake, mesh, and fabric solutions using Databricks, Cloudera, Snowflake, Hadoop, and cloud-native services.
• Establish data governance, metadata, lineage, security, access control, quality, observability, compliance, and operational reliability standards.
• Design scalable ETL/ELT frameworks, data pipelines, and integration patterns for batch, streaming, and real-time processing; guide engineering teams and optimize performance, reliability, and cost.
• Lead cloud architecture, migration, modernization, and hybrid or multi-cloud initiatives; define IaC, CI/CD, DevOps, platform engineering, governance, and FinOps practices.
• Set enterprise AI/ML strategy and architecture, including MLOps, generative AI, agentic AI, RAG, LLMs, vector databases, AI governance, responsible AI, and model-risk practices.
• Define API and enterprise integration strategy, designing secure and maintainable API-first, microservices, event-driven, and distributed architectures.
• Establish API governance and lifecycle standards, and integration patterns using REST, GraphQL, ESB, messaging, and streaming technologies.
• Define quality engineering and test strategies across data, cloud, APIs, applications, and AI/ML; promote automated, CI/CD-integrated testing and continuous validation.
• Advise executive, business, technology, and customer stakeholders; translate strategic objectives into technology solutions and communicate architecture decisions clearly.
• Mentor architects, engineers, technical leads, and development teams; lead architecture boards, governance forums, and design discussions, and promote relevant innovation.

Technologies:

• Agentic AI
• AI
• API
• AWS
• Architect
• Azure
• CI/CD
• Cloud
• Databricks
• DevOps
• Docker
• ESB
• ETL
• Fabric
• GitHub
• GitLab
• GraphQL
• Hadoop
• Support
• Jenkins
• Kafka
• Kubernetes
• Machine Learning
• MLOps
• NoSQL
• Oracle
• PostgreSQL
• PySpark
• RAG
• REST
• SQL
• Security
• Snowflake
• Spark
• Terraform
• microservices
• Business Intelligence
• Data Warehouse
• GCP
• Hive
• Web
• Yarn

More

We at Tanisha Systems are seeking an Enterprise Architect focused on Data, Cloud, and AI to shape enterprise technology strategy and support large-scale digital, data, and AI transformation. The role partners with executive leaders, business stakeholders, engineering teams, architects, and customers. It is based onsite in Scottsdale, Arizona, or San Francisco, California, and is offered as a contract-to-hire opportunity. We are an Equal Employment Opportunity Employer and provide reasonable accommodation during the application and hiring process upon request.

last updated 43 week of 2026