Azure Data Architect
New
Based in the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLCI/CDData modelingAzure DevOpsPySpark
Requirements
- 5+ years of hands-on experience as a Data Architect, Senior Data Engineer, or similar role within Azure environments.
- Deep expertise in Azure Databricks, including Unity Catalog, Delta Lake, cluster optimization, and workspace administration.
- Strong experience with Microsoft Fabric, including Data Factory, Data Warehouse, OneLake, and Power BI integrations.
- Proven experience leading multiple large-scale cloud migration projects involving enterprise data platforms.
- Advanced proficiency in PySpark, SQL, Python, and modern data processing frameworks.
- Hands-on experience with Azure services such as Data Lake Storage Gen2, Synapse Analytics, Data Factory, Event Hubs, and Key Vault.
- Strong understanding of data modeling concepts, including dimensional modeling, star schemas, data vault, and database design principles.
- Experience implementing CI/CD processes for data workloads using Azure DevOps, GitHub Actions, or similar tools.
- Prior client-facing consulting or solution architecture experience with the ability to engage business and technical stakeholders.
- Excellent communication, presentation, and workshop facilitation skills.
- Ability to manage multiple priorities, work independently, and drive complex projects to completion.
Responsibilities
- Design and implement scalable, secure, and high-performance data architectures using Azure Databricks, Microsoft Fabric, Delta Lake, Unity Catalog, and OneLake.
- Lead end-to-end cloud migration projects, transitioning legacy data platforms and on-premises environments into Azure-native solutions.
- Develop and optimize ETL/ELT pipelines using Azure Data Factory, Databricks workflows, and Fabric Data Pipelines.
- Build real-time data processing solutions using technologies such as Event Hubs, Stream Analytics, and Databricks Structured Streaming.
- Create optimized data models, queries, and transformation processes using SQL, Python, PySpark, and Spark SQL.
- Establish data governance frameworks, security standards, compliance practices, and technical reference architectures.
- Present architecture proposals and technical recommendations to stakeholders, including executive audiences.
- Provide mentorship, documentation, and knowledge transfer to client teams and internal stakeholders.
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