Job DescriptionAbout Position:We are seeking a highly experienced Enterprise Architect to define and drive the enterprise technology strategy across Data Platforms, Cloud, Cloudera, 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. This role will collaborate closely with executive leadership, business stakeholders, engineering teams, and customers to architect enterprise-scale digital, data, and AI platforms that maximize business value, operational efficiency, scalability, and innovation. The successful candidate will serve as a strategic technology leader, driving enterprise architecture governance, modernization initiatives, cloud adoption, and next-generation AI-driven transformation programs.
- Role: Enterprise Architect
- Location: Scottsdale, Arizona (USA)
- Experience: Between 12 to 16 Years
- Job Type: Full Time Employment
What You'll Do: - Define enterprise-wide architecture standards, reference architectures, technology blueprints, and roadmap strategies.
- Lead architecture governance, solution reviews, and enterprise technology decision-making processes.
- Design scalable, resilient, secure, and cost-optimized enterprise platforms.
- Align technology investments and architecture strategies with business goals and digital transformation initiatives.
- Drive cloud adoption, platform modernization, and enterprise engineering programs.
- Establish technology standards, best practices, and architectural governance frameworks.
- Architect enterprise data platforms using Databricks, Snowflake, Hadoop, Cloudera, and cloud-native services.
- Design modern Lakehouse, Data Warehouse, Data Lake, Data Mesh, and Data Fabric architectures.
- Define enterprise data governance, metadata management, lineage, cataloging, and security frameworks.
- Establish data quality, observability, compliance, and monitoring standards.
- Design structured, semi-structured, and unstructured data management strategies.
- Drive enterprise data modernization initiatives and platform consolidation efforts.
- Architect large-scale ETL and ELT frameworks supporting batch and real-time processing workloads.
- Design and oversee scalable data pipelines across diverse enterprise data sources.
- Define data integration patterns using Spark, PySpark, Hadoop ecosystem technologies, and cloud-native services.
- Establish best practices for data ingestion, orchestration, transformation, and delivery.
- Optimize scalability, performance, reliability, and cost efficiency of enterprise data platforms.
- Drive adoption of modern data engineering practices and automation frameworks.
- Design enterprise cloud solutions across AWS, Microsoft Azure, and Google Cloud Platform.
- Lead cloud migration and application modernization initiatives.
- Architect highly available, scalable, resilient, and secure cloud-native platforms.
- Define Infrastructure as Code (IaC), DevOps, CI/CD, and automation strategies.
- Establish cloud governance, security, networking, compliance, and FinOps best practices.
- Drive platform engineering initiatives for enterprise-scale environments.
- Define enterprise AI and Machine Learning architecture strategies.
- Architect MLOps frameworks and model lifecycle management solutions.
- Design Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), and LLM integration architectures.
- Establish AI governance, security, compliance, monitoring, and responsible AI practices.
- Enable predictive analytics, business intelligence, advanced analytics, and AI-powered decision-making platforms.
- Guide adoption of emerging AI technologies and enterprise AI transformation initiatives.
- Define enterprise integration architecture and API strategies.
- Design Microservices, Event-Driven, and API-First architectures.
- Establish integration patterns leveraging REST APIs, GraphQL, messaging systems, and streaming platforms.
- Ensure secure, scalable, reusable, and governed enterprise integrations.
- Drive modernization of legacy integration ecosystems.
- Define enterprise testing strategies across data, cloud, API, and application ecosystems.
- Architect automated testing frameworks for ETL, Data Quality, APIs, AI/ML platforms, and cloud solutions.
- Drive adoption of CI/CD-integrated quality engineering practices.
- Establish reliability engineering, observability, resiliency testing, and performance testing standards.
- Promote automation-driven quality assurance and operational excellence.
- Act as a trusted technology advisor to executive leadership and key business stakeholders.
- Lead architecture review boards, governance councils, and technical strategy forums.
- Mentor solution architects, technical leads, engineers, and data architects.
- Drive innovation initiatives and evaluation of emerging technologies.
- Build strong partnerships with business, engineering, product, and customer teams.
- Influence enterprise technology direction and long-term digital transformation strategies.
Expertise You'll Bring:- 12 to 16 years of experience in Enterprise Architecture, Data Architecture, Cloud Architecture, or Technology Leadership roles.
- Extensive experience designing enterprise-scale data platforms and cloud-native solutions.
- Strong expertise in Databricks Lakehouse architecture and implementation.
- Hands-on experience with Snowflake enterprise data platforms.
- Deep knowledge of Cloudera and Hadoop ecosystem technologies including HDFS, Hive, Spark, and YARN.
- Expertise in Data Warehouse, Data Lake, Lakehouse, Data Mesh, and Data Fabric architectures.
- Strong experience in Data Engineering, ETL/ELT architecture, and enterprise-scale data pipelines.
- Advanced knowledge of Apache Spark, PySpark, Kafka, streaming, and real-time processing frameworks.
- Experience implementing data quality, observability, lineage, governance, and metadata management solutions.
- Strong knowledge of AWS, Azure, and Google Cloud Platform services and architecture patterns.
- Experience defining Infrastructure as Code strategies using Terraform, CloudFormation, or equivalent platforms.
- Strong understanding of cloud security, networking, governance, compliance, and FinOps principles.
- Experience designing AI/ML platforms, MLOps frameworks, and machine learning lifecycle management solutions.
- Knowledge of Generative AI, Large Language Models (LLMs), Agentic AI, Vector Databases, and RAG architectures.
- Strong expertise in API management, Microservices, Event-Driven Architecture, GraphQL, and enterprise integrations.
- Hands-on experience with DevOps, CI/CD pipelines, GitHub, GitLab, Jenkins, Docker, and Kubernetes.
- Experience architecting enterprise testing, automation, data validation, and quality engineering frameworks.
- Strong expertise with SQL Server, Snowflake, PostgreSQL, Oracle, and NoSQL databases.
- Proven track record of leading enterprise modernization and digital transformation programs.
- Excellent communication, leadership, stakeholder management, and executive presentation skills.
Benefits:- Competitive salary and benefits package
- Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
- Opportunity to work with cutting-edge technologies
- Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
- Annual health check-ups
- Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents
