DescriptionAzure Data ArchitectPosition OverviewWe are seeking an experienced Azure Data Architect with deep hands-on expertise in cloud data migration, scalable architecture design, and modern data platforms. This role requires a technical leader who can architect and implement enterprise-scale data solutions while working directly with clients to translate business requirements into robust technical solutions.
Key ResponsibilitiesArchitecture & Technical Leadership- Design and implement scalable, high-performance data architectures on Azure Databricks and Microsoft Fabric
- Lead end-to-end cloud migration projects, moving on-premises data platforms to Azure-native solutions
- Build data Lakehouse architectures leveraging Delta Lake, Unity Catalog, and Fabric OneLake
- Establish data governance frameworks, security protocols, and compliance standards across cloud environments
- Define technical standards, best practices, and reference architectures for data solutions
Hands-On Implementation- Develop and optimize ETL/ELT pipelines using Azure Data Factory, Databricks workflows, and Fabric Data Pipelines
- Implement real-time streaming architectures using Event Hubs, Stream Analytics, and Databricks Structured Streaming
- Build performance-optimized data models and queries in SQL, PySpark, and Spark SQL
- Configure and optimize Azure resources including storage accounts, compute clusters, and networking
- Troubleshoot complex technical issues across the entire data stack
Client Engagement & Consulting- Serve as a trusted technical advisor to clients, understanding their business challenges and data strategy goals
- Lead discovery workshops and architecture design sessions with stakeholders and technical teams
- Present technical recommendations and architecture proposals to executive leadership
- Provide hands-on mentorship and knowledge transfer to client teams
- Manage multiple client engagements simultaneously while maintaining high-quality delivery
Migration Expertise- Assess legacy systems and develop comprehensive migration strategies and roadmaps
- Execute large-scale data migrations from on-premises databases, Hadoop clusters, and other cloud platforms to Azure
- Implement data replication, synchronization, and validation strategies during migration
- Minimize downtime and risk through phased migration approaches and rollback procedures
Required QualificationsTechnical Skills- 5+ years of hands-on experience as a data architect or senior data engineer in 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 integration
- Proven track record of leading and executing 3+ cloud migration projects involving large-scale data platforms
- Expert-level proficiency in PySpark, SQL, and Python for data processing and transformation
- Hands-on experience with Azure services: Data Lake Storage Gen2, Synapse Analytics, Data Factory, Event Hubs, Key Vault
- Strong understanding of data modeling (star schema, dimensional modeling, data vault) and database design principles
- Experience implementing CI/CD pipelines for data workloads using Azure DevOps or GitHub Actions
Consulting & Soft Skills- 3+ years of client-facing consulting experience in a professional services or solution architect role
- Excellent communication skills with ability to explain complex technical concepts to non-technical audiences
- Demonstrated ability to gather requirements, manage stakeholder expectations, and drive consensus
- Strong presentation and workshop facilitation skills
- Experience managing competing priorities across multiple client engagements
- Self-motivated with ability to work independently and drive projects to completion
Preferred Qualifications- Microsoft Azure certifications (DP-203, AZ-305, or equivalent)
- Databricks certification (Associate or Professional level)
- Experience with data governance tools (Purview, Unity Catalog)
- Knowledge of machine learning operations (MLOps) and ML platforms
- Experience with infrastructure-as-code (Terraform, Bicep)
- Background in specific industries such as financial services, healthcare, retail, or manufacturing
