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About the role
As a senior technical lead, your role will involve designing, scaling, and governing enterprise-grade data platforms across Microsoft Fabric, Databricks, and Snowflake. You will be responsible for defining data architecture standards, enabling AI/GenAI-ready platforms, leading engineering teams, and delivering secure, high-performance cloud data solutions that support analytics and business outcomes. Key Responsibilities: - Lead the design and implementation of scalable data platforms using Microsoft Fabric, Databricks, and Snowflake including Pipelines, Notebooks, Lakehouse, Data Warehouse, and Semantic Models. - Define end-to-end data architecture standards, patterns, and best practices across ingestion, storage, transformation, modeling, and consumption layers. - Guide technical decisions on compute patterns, storage optimization, pipeline orchestration, and data modeling frameworks. - Evaluate and integrate emerging technologies to modernize the platform and enable AI/GenAI workloads. - Partner with AI/ML teams to productionize models and integrate them with enterprise data workflows. - Ensure data governance, lineage tracking, and metadata standards to support trustworthy AI initiatives. - Champion data governance, security, privacy, and compliance requirements within the platform. - Implement observability frameworks for pipeline monitoring, performance tuning, and reliability engineering. - Serve as the primary technical point of contact for data platform projects and stakeholders. - Communicate technical roadmaps, project risks, and delivery plans clearly and effectively. - Develop and deliver dashboards and reports using Power BI and Tableau. Qualifications Required: - Bachelors or Masters degree in Computer Science, Engineering, Data Science, or equivalent professional experience. - 12+ years of experience in data engineering, data platform development, or cloud data architecture. - Mandatory deep hands-on expertise with Microsoft Fabric, Snowflake, or Databricks Data Warehouse. - Strong proficiency in PySpark, distributed compute, and data transformation frameworks. - Advanced SQL capabilities and experience building stored procedures for transactional and analytical workloads. - Proven track record in designing and delivering large-scale data platforms in cloud environments (Azure preferred). - Solid understanding of AI/ML data workflows, GenAI dataset preparation, and integration patterns. - Demonstrated ability to lead engineering teams, drive architectural decisions, and oversee complex technology implementations. - Proficiency in creating interactive dashboards and reports using Power BI and Tableau. As a senior technical lead, your role will involve designing, scaling, and governing enterprise-grade data platforms across Microsoft Fabric, Databricks, and Snowflake. You will be responsible for defining data architecture standards, enabling AI/GenAI-ready platforms, leading engineering teams, and delivering secure, high-performance cloud data solutions that support analytics and business outcomes. Key Responsibilities: - Lead the design and implementation of scalable data platforms using Microsoft Fabric, Databricks, and Snowflake including Pipelines, Notebooks, Lakehouse, Data Warehouse, and Semantic Models. - Define end-to-end data architecture standards, patterns, and best practices across ingestion, storage, transformation, modeling, and consumption layers. - Guide technical decisions on compute patterns, storage optimization, pipeline orchestration, and data modeling frameworks. - Evaluate and integrate emerging technologies to modernize the platform and enable AI/GenAI workloads. - Partner with AI/ML teams to productionize models and integrate them with enterprise data workflows. - Ensure data governance, lineage tracking, and metadata standards to support trustworthy AI initiatives. - Champion data governance, security, privacy, and compliance requirements within the platform. - Implement observability frameworks for pipeline monitoring, performance tuning, and reliability engineering. - Serve as the primary technical point of contact for data platform projects and stakeholders. - Communicate technical roadmaps, project risks, and delivery plans clearly and effectively. - Develop and deliver dashboards and reports using Power BI and Tableau. Qualifications Required: - Bachelors or Masters degree in Computer Science, Engineering, Data Science, or equivalent professional experience. - 12+ years of experience in data engineering, data platform development, or cloud data architecture. - Mandatory deep hands-on expertise with Microsoft Fabric, Snowflake, or Databricks Data Warehouse. - Strong proficiency in PySpark, distributed compute, and data transformation frameworks. - Advanced SQL capabilities and experience building stored procedures for transactional and analytical workloads. - Proven track record in designing and delivering large-scale data platforms in cloud environments (
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