BI Architect
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Role details
Tech stack
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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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