Principal Data Architect - R01556905

Principal Data Architect

• Fabric, Azure Data engineering, ADF,

• Azure Data EngineerIng Basic: Principal Data Architect

• About the Role:

• Define and implement end-to-end Azure data architecture leveraging ADLS Gen2, ADF, Synapse, Databricks, and Microsoft Fabric.
• Lead the design and modernization of enterprise data platforms, enabling scalable, secure, and cost-effective data solutions.
• Partner with business and technology stakeholders to translate analytical and reporting needs into technical designs.
• Architect data lakehouse and warehouse solutions aligned with data governance, cataloging, and lineage frameworks.
• Evaluate and implement data integration, transformation, and orchestration patterns for high-volume data workloads.
• Drive data platform standardization, automation, and CI/CD practices across projects.
• Provide technical leadership and mentorship to engineers and data modelers.
• Collaborate with cross-functional teams to ensure data security, compliance, and performance optimization.
• Stay current on emerging Azure and Microsoft Fabric capabilities to drive innovation and continuous improvement.

• 14+ years of experience in data engineering, architecture, or analytics, with at least 6+ years on Azure data services.
• Strong hands-on expertise with:
• Azure Data Lake Storage (ADLS) Gen2
• Azure Data Factory (ADF)
• Azure Synapse Analytics
• Microsoft Fabric (Data Engineering / Data Warehouse / Data Activator)
• Databricks / PySpark / Power BI (preferred)
• Experience designing data lakehouse, ELT pipelines, and real-time data solutions.
• Proven experience in solution architecture, cost optimization, and performance tuning.
• Familiarity with data governance, security, and metadata management frameworks.
• Excellent stakeholder management, communication, and leadership skills.
• Azure certifications (e.g., Azure Solutions Architect Expert, Data Engineer Associate) are a strong plus.

• Experience in retail, logistics, BFSI, or manufacturing domains.
• Exposure to data mesh or data fabric concepts and implementations.
• Prior experience in leading large modernization or migration programs.