Enterprise Architect – Data, Cloud & AI

Hi,

Hope You are doing well.

This is Piyush from Tanisha Systems. I have a job opportunity for you, if you are interested, please share your Resume and details ASAP.

Enterprise Architect – Data, Cloud & AI

Location

Scottsdale, AZ / San Francisco, CA – Onsite

Hire Type

Contract-to-Hire (CTH)

Must-Have Skills

Databricks | Cloudera | Snowflake | Data Engineering

Role Overview

We are seeking a highly experienced Enterprise Architect to define and drive enterprise technology strategy across Data Platforms, Cloud, AI/ML, Analytics, and Enterprise Integration.

The ideal candidate will have strong hands-on architecture experience with Databricks, Cloudera, Snowflake, Hadoop, Data Engineering, and Cloud Platforms, along with the ability to design scalable, secure, resilient, and future-ready enterprise solutions.

This role will work closely with executive leadership, business stakeholders, engineering teams, architects, and customers to define enterprise architecture, establish technology standards, drive modernization, and deliver large-scale digital, data, and AI transformation initiatives.

Key Responsibilities

Enterprise Architecture & Technology Strategy

• Define enterprise-wide architecture standards, reference architectures, technology principles, and strategic technology roadmaps.
• Lead architecture governance, solution reviews, technology evaluations, and architecture decision processes.
• Design scalable, resilient, secure, highly available, and cost-optimized enterprise platforms.
• Align enterprise technology architecture with business objectives, digital transformation strategies, and long-term organizational goals.
• Drive cloud adoption, legacy modernization, platform engineering, and enterprise transformation initiatives.
• Evaluate emerging technologies and recommend solutions that provide measurable business and operational value.

Data Platform Architecture

• Architect enterprise-scale data platforms using Databricks, Cloudera, Snowflake, Hadoop, and cloud-native data services.
• Design and implement modern Lakehouse, Data Warehouse, Data Lake, Data Mesh, and Data Fabric architectures.
• Define enterprise data governance, metadata management, data lineage, security, and access-control frameworks.
• Establish standards for data quality, observability, monitoring, compliance, and operational reliability.
• Develop strategies for managing structured, semi-structured, and unstructured enterprise data.
• Define scalable data architecture patterns supporting analytics, AI/ML, reporting, and business intelligence.

Data Engineering & ETL Architecture

• Architect large-scale ETL/ELT frameworks supporting batch, streaming, and real-time data processing.
• Lead the architecture of scalable data pipelines integrating multiple enterprise source systems.
• Define data integration and processing patterns using Apache Spark, PySpark, Databricks, Cloudera/Hadoop, Kafka, and cloud-native services.
• Establish best practices for data ingestion, transformation, orchestration, processing, and delivery.
• Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
• Provide architectural guidance to data engineering teams on modern data processing and integration patterns.

Cloud Architecture

• Design enterprise solutions across AWS, Microsoft Azure, and Google Cloud Platform (GCP).
• Lead cloud migration, modernization, and hybrid/multi-cloud architecture initiatives.
• Architect highly available, secure, scalable, and resilient cloud platforms.
• Define Infrastructure as Code (IaC), CI/CD, DevOps, and platform engineering strategies.
• Establish cloud governance standards covering security, networking, identity, monitoring, compliance, and cost management.
• Promote FinOps and cloud cost-optimization practices across enterprise platforms.

AI/ML & Advanced Analytics

• Define enterprise-wide AI/ML architecture and technology strategy.
• Architect MLOps frameworks supporting model development, deployment, monitoring, and lifecycle management.
• Design architectures for Generative AI, Agentic AI, RAG, LLMs, and enterprise AI applications.
• Define integration patterns for LLMs, vector databases, knowledge bases, and AI services.
• Establish AI governance, security, monitoring, responsible AI, and model-risk management practices.
• Enable predictive analytics, business intelligence, advanced analytics, and AI-driven business capabilities.

API & Enterprise Integration

• Define enterprise integration architecture and API strategy.
• Design API-first, microservices, event-driven, and distributed architectures.
• Establish integration patterns using REST APIs, GraphQL, Enterprise Service Bus (ESB), messaging systems, and streaming platforms.
• Ensure enterprise integrations are secure, scalable, reusable, resilient, and maintainable.
• Define standards for API governance, lifecycle management, security, monitoring, and observability.

Quality Engineering & Test Automation

• Define enterprise quality engineering and testing strategies across data, cloud, APIs, applications, and AI/ML platforms.
• Architect automated testing frameworks for ETL, data quality, APIs, cloud platforms, and AI/ML solutions.
• Drive adoption of CI/CD-integrated testing and quality engineering practices.
• Establish standards for reliability, performance, scalability, observability, and resilience testing.
• Promote automated validation and continuous quality across enterprise platforms.

Leadership & Stakeholder Management

• Serve as a trusted technology advisor to executive, business, and technology leadership.
• Partner with customers and business stakeholders to understand strategic objectives and translate them into technology solutions.
• Mentor architects, engineers, technical leads, and development teams.
• Lead architecture review boards, technical governance forums, and design discussions.
• Communicate complex technical concepts and architectural decisions effectively to both technical and executive audiences.
• Drive innovation and adoption of emerging technologies aligned with business strategy.

Required Technical Skills

Data Platforms

• Databricks Lakehouse
• Cloudera
• Snowflake
• Hadoop Ecosystem – HDFS, Hive, Spark, YARN
• Data Lakes & Data Warehouses
• Delta Lake
• Data Mesh / Data Fabric

Data Engineering

• ETL / ELT Architecture
• Enterprise Data Pipelines
• Apache Spark / PySpark
• Kafka
• Batch & Real-Time Processing
• Streaming Architecture
• Data Quality & Observability

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Cloud Security & Networking
• Infrastructure as Code – Terraform / CloudFormation
• Cloud Architecture & Migration

AI/ML

• Machine Learning Platforms
• MLOps
• Generative AI
• Large Language Models (LLMs)
• Agentic AI
• RAG Architectures
• Vector Databases
• AI Governance

API & Integration

• REST APIs
• GraphQL
• Enterprise Service Bus (ESB)
• Event-Driven Architecture
• Microservices
• Messaging & Streaming Frameworks
• API Management

DevOps & Automation

• CI/CD Pipelines
• GitHub / GitLab
• Jenkins
• Docker
• Kubernetes
• Infrastructure Automation
• Test Automation Frameworks

Database Technologies

• Snowflake
• SQL Server
• PostgreSQL
• Oracle
• NoSQL Databases
• Enterprise Data Warehousing

Preferred Experience

• Experience leading enterprise-wide data modernization and cloud transformation programs.
• Strong background in Databricks, Cloudera, Snowflake, and Hadoop-based ecosystems.
• Experience designing large-scale data platforms for analytics, AI/ML, and enterprise reporting.
• Experience working with distributed systems, high-volume data processing, and real-time streaming.
• Experience with enterprise architecture frameworks, governance models, and technology roadmaps.
• Consulting or customer-facing architecture experience is highly desirable.

Soft Skills

• Executive stakeholder management
• Strategic thinking and technology vision
• Enterprise architecture leadership
• Strong communication and presentation skills
• Technical consulting and customer engagement
• Problem-solving and decision-making
• Ability to influence across business and technology teams
• Strong leadership, collaboration, and mentoring skills

Piyush Chowdhary

Sr. Delivery Manager/Account Manager

Tanisha Systems Inc

Desk no. 732-944-0375

Email

piyush.chowdhary@tanishasystems.com

Web

www.tanishasystems.com

Linkedin URL

Piyush Chowdhary - Irvine, California, United States | Professional Profile | LinkedIn

Address:99 Wood Ave South Suite # 308,Iselin, NJ 08830

E-Verify, Certified Minority Business Enterprise MBE, Dun & Bradstreet CREDIBILITY

"Tanisha Systems, Inc. is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, (including pregnancy, childbirth, or related medical conditions), sexual orientation, national origin, *, physical or mental disability, or any other status protected by applicable federal, state, or local law. We are committed to providing an accessible work environment for all candidates. Reasonable accommodation will be provided during the application and hiring process upon request."