BI Architect

OpenKyber LLC
Scottsdale, AZ, United States
21 days ago
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Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Data Analysis Microsoft Azure Cloud Computing Cloud Computing Security Continuous Integration Information Engineering Data Governance Extract Transform Load (ETL) Data Warehousing
+54 more
DevOps Github Apache Hadoop Hadoop Distributed File System Apache Hive PostgreSQL Machine Learning Enterprise Messaging Systems Meta-Data Management Microsoft SQL Server NoSQL Oracle (Applications) Data Mesh SQL Databases Software Testing Automation Framework Data Streaming Tableau (Software) Unstructured Data Enterprise Data Management Google Cloud Performance Testing Real Time Systems Apache Yarn Azure Data Factory Retrieval-Augmented Generation Large Language Models Snowflake Apache Spark Generative AI Infrastructure as Code (IaC) Agentic-AI Gitlab Cloudformation Event Driven Architecture Microsoft Fabric Data Lakes Pyspark Kubernetes Enterprise Integration Apache Kafka Graphql Data Management Machine Learning Operations Data Delivery Api Design Restful APIs Terraform Data Pipelines Serverless Computing Enterprise Service Bus Docker Jenkins Databricks Microservices

Job description

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

  • 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.

Required Technical Skills

  • 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
  • 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
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Requirements

  • Executive stakeholder management
  • Strategic thinking
  • Architectural leadership
  • Strong communication and presentation skills
  • Problem-solving and decision-making
  • Customer engagement and consulting experience

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