Bi Architect

Role : Enterprise Architect Location : Scottsdale, AZ (Onsite)

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.

• 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.

• 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.

• 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 the performance and scalability of enterprise data pipelines.

• 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.

• 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.

• 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.

• 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.

• 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.

• Databricks Lakehouse
• Snowflake
• Hadoop Ecosystem (HDFS, Hive, Spark, YARN)
• Data Warehouse & Data Lake Platforms
• Delta Lake
• Data Mesh & Data Fabric

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

• AWS
• Microsoft Azure
• Google Cloud Platform (Google Cloud Platform)
• Cloud Security & Networking
• Infrastructure as Code (Terraform, CloudFormation)

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

• REST APIs
• GraphQL
• Enterprise Service Bus (ESB)
• Event-Driven Architecture
• Microservices

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

• Snowflake
• SQL Server
• PostgreSQL
• Oracle
• NoSQL Databases

• 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.

For applications and inquiries,