Azure Architect
- Canada
Contract
Applications open in a new tab.
Job details
- Job type
- Contract
- Posting language
- English
- Posted
Original job description
- Should have 15+ years of experience with last 4 years in implementing Cloud native end-to-end Data Solutions from ingestion to consumption to support variety of needs such as Modern Data warehouse, BI, Insights and Analytics
- Should have experience in architecture and implementing End to End Modern Data Solutions using Azure and advance data processing frameworks like Databricks etc.
- Experience with Databricks, PySpark, and modern data platforms.
- Proficiency in cloud-native architecture and data governance.
- Strong experience in migrating from on premises to cloud solutions (Spark, Hadoop to Databricks).
- Understanding of Agile/Scrum methodologies.
- Demonstrated knowledge of data warehouse concepts. Strong understanding of Cloud native databases, columnar database architectures
- Ability to work with Data Engineering teams, Data Management Team, BI and Analytics in a complex development IT environment.
- Good appreciation and at least one implementation experience on processing substrates in Data Engineering - such as ETL Tools, Kafka, ELT techniques
- Data Mesh and Data Products designing, and implementation knowledge will be an added advantage.
Responsibilities:
- Develop modern data solutions and architecture for cloud-native data platforms.
- Build cost-effective infrastructure in Databricks and orchestrate workflows using Databricks/ADF.
- Lead data strategy sessions focused on scalability, performance, and flexibility.
- Build CI/CD pipelines for Databricks in Azure DevOps.
- Collaborate with customers to implement solutions for data modernization.
- Create training plans and learning materials to upskill VM associates.
- Develop industry-specific and domain-oriented solutions for customer data needs.
- Build a smart operations framework for DataOps and MLOps.
More about this job
Responsibilities
Design and deliver cloud-native data solutions, including Databricks infrastructure, data workflows, and CI/CD pipelines in Azure. Lead data strategy and modernization efforts, collaborate with customers and engineering teams, develop training materials, and establish DataOps and MLOps frameworks.
Requirements
Requires 15+ years of experience, including the last four years implementing end-to-end cloud-native data solutions, with strong expertise in Azure, Databricks, PySpark, and modern data platforms. Candidates should also have experience with data governance, on-premises-to-cloud migration, data warehousing, cloud-native databases, and Agile/Scrum; Data Mesh and Data Products experience is an advantage.
Skills
- Azure
- Databricks
- PySpark
- Cloud-Native Architecture
- Data Engineering
- Data Governance
- Data Warehousing
- Data Migration
- ETL
- Kafka
- Azure Data Factory
- Azure DevOps
- CI/CD
- DataOps
- MLOps
- Agile/Scrum
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Data & Analytics
- Software
- Consulting
- Management & Leadership
Keywords
- Azure
- Databricks
- PySpark
- Modern Data Platforms
- Cloud-Native Data Solutions
- Data Engineering
- Data Governance
- Modern Data Warehouse
- Business Intelligence
- Analytics
- Data Migration
- Spark
- Hadoop
- ETL
- ELT
- Kafka
- Data Mesh
- Data Products
- Azure Data Factory
- Azure DevOps
- CI/CD Pipelines
- Cloud-Native Databases
- Columnar Database Architecture
- Agile
- Scrum
- DataOps
- MLOps
- Workflow Orchestration
- Data Modernization