Data Enterprise Architect

Role : Enterprise Architect Location : Scottsdale AZ / San Francisco CA (Onsite) 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/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. ______________________________________ 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 ______________________________________ 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.