Azure Databricks Architect
- Toronto, ON, Canada
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- English
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Original job description
Role Overview
Habilelabs is seeking an experienced Lead Architect with strong expertise in Microsoft Azure, Databricks, and modern Data & AI platforms. This role will design and deliver scalable, secure, high-performing enterprise data solutions while working closely with business stakeholders, engineering teams, and clients.
Key Responsibilities
- Architect end-to-end data and analytics solutions on Azure and Databricks.
- Design scalable platforms supporting batch, streaming, and real-time analytics.
- Lead solution design discussions, architecture reviews, and technical governance.
- Define data lake, data warehouse, lakehouse, and data mesh architectures.
- Translate business requirements into practical technical solutions.
- Establish platform security, governance, and compliance standards.
- Design data integration frameworks using Azure-native services and Databricks.
- Drive performance optimization, cloud cost management, and modernization initiatives.
- Provide technical leadership and mentor engineering teams.
- Support proposal development, effort estimation, and client presentations.
- Ensure alignment with enterprise architecture standards and best practices.
Required Technical Skills
- Azure: Azure Data Factory, Azure Databricks, ADLS Gen2, Azure Synapse Analytics, Azure SQL Database, Azure Event Hub, Azure Service Bus, Azure Functions, Azure Key Vault, Azure Monitor, and Microsoft Entra ID.
- Databricks: Lakehouse Architecture, Delta Lake, Unity Catalog, Databricks Workflows, Structured Streaming, Medallion Architecture, cluster optimization, and performance tuning.
- Data Engineering: Python, PySpark, SQL, data modeling, ETL/ELT frameworks, data warehousing, and real-time data processing.
- DevOps and Automation: Azure DevOps, CI/CD pipelines, Git, and Infrastructure as Code. Terraform is preferred.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
- 10+ years of experience in Data Engineering, Cloud Architecture, or Solution Architecture.
- 5+ years of hands-on experience with Azure cloud services.
- 4+ years of hands-on experience with Databricks and Spark-based solutions.
- Demonstrated experience designing enterprise-scale data platforms.
- Experience working with large-scale structured and unstructured datasets.
- Strong stakeholder management and client-facing communication skills.
More about this job
Responsibilities
Architect end-to-end Azure and Databricks data platforms for batch, streaming, and real-time analytics, including lakehouse, warehouse, and data mesh solutions. Lead architecture reviews and governance, establish security and compliance standards, optimize performance and cloud costs, and mentor teams while supporting client proposals and presentations.
Requirements
Requires a bachelor's or master's degree in a related field, 10+ years of experience in data engineering or cloud/solution architecture, 5+ years with Azure, and 4+ years with Databricks and Spark. Candidates should have enterprise-scale platform design experience, familiarity with large structured and unstructured datasets, and strong stakeholder management and client communication skills.
Skills
- Microsoft Azure
- Azure Databricks
- Azure Data Factory
- ADLS Gen2
- Azure Synapse Analytics
- Delta Lake
- Unity Catalog
- Lakehouse Architecture
- Structured Streaming
- Python
- PySpark
- SQL
- Data Modeling
- Azure DevOps
- CI/CD
- Terraform
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Management & Leadership
- Consulting
Keywords
- Microsoft Azure
- Azure Data Factory
- Azure Databricks
- ADLS Gen2
- Azure Synapse Analytics
- Azure SQL Database
- Azure Event Hub
- Azure Service Bus
- Azure Functions
- Azure Key Vault
- Azure Monitor
- Microsoft Entra ID
- Lakehouse Architecture
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Structured Streaming
- Medallion Architecture
- Python
- PySpark
- SQL
- Data Modeling
- ETL/ELT
- Data Warehousing
- Azure DevOps
- CI/CD
- Git
- Infrastructure as Code
- Terraform
- Data Mesh