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Area(s) of responsibilityRole Summary We are seeking a seasoned Senior Azure Data Engineer / Sr. Technical Lead with extensive expertise in Azure Databricks, PySpark, ADF, SQL, and modern data engineering practices. This role requires solid technical leadership, hands-on engineering capabilities, and the ability to design, architect, and deliver enterprise-scale data solutions. The ideal candidate will lead complex data initiatives, mentor engineering teams, and collaborate with cross-functional stakeholders to build a robust and scalable data ecosystem on Azure. Key Responsibilities 1. Solution Architecture & Technical Leadership - Lead the design, development, and deployment of large-scale data engineering solutions using Azure Databricks, PySpark, SQL, ADF, and Azure Data Lake. - Architect end-to-end Modern Data Warehouse (MDW) and Lakehouse solutions, ensuring scalability, performance, security, and cost optimization. - Define technical standards, coding best practices, reusable frameworks, and architectural guidelines for engineering teams. - Provide technical leadership across the project lifecycle-requirements analysis, solution blueprinting, estimation, development, and deployment. - Data Pipeline Engineering - Build, optimize, and maintain scalable, high-performance ELT/ETL pipelines to process large volumes of structured and unstructured data. - Set up complex data ingestion frameworks, enabling seamless integration with on-premise systems, cloud services, APIs, and third-party sources. - Ensure high availability, data reliability, and error-resilient orchestration workflows in Azure Data Factory. - Azure Databricks & PySpark Expertise - Design and implement advanced transformation logic using PySpark on Databricks, ensuring efficient data processing and code modularity. - Utilize Delta Lake capabilities-ACID transactions, schema evolution, versioning, time travel-to manage enterprise-grade datasets. - Perform cluster-level tuning, optimization of shuffle operations, caching, partitioning, and job parallelization. - Manage Databricks job pipelines, notebooks, clusters, job scheduling, and integration with CI/CD pipelines. Mandatory Skills & Experience - 10-13 years of overall experience in data engineering and enterprise data platforms. - Minimum 3 years of hands-on project experience in Azure Databricks (beyond POCs). - Minimum 5 years of experience building and orchestrating pipelines in Azure Data Factory (ADF). - Minimum 2+ years of strong PySpark experience with complex data transformation logic. - 6+ years of ETL & Data Warehouse experience, including dimensional modelling, data partitioning, and performance optimization. - Strong SQL expertise-complex queries, optimization, stored procedures, analytical functions. - Proven experience working with Azure Data Lake Storage (ADLS), Delta Lake, and modern data processing patterns. Good-to-Have Skills - Experience working in Agile/Scrum environments, including sprint planning and backlog management. - Knowledge of Azure Synapse, Event Hub, Databricks workflows, and Azure DevOps CI/CD. - Databricks certifications (Associate/Professional) or Azure certifications (DP 203/DP 900). Locations - Country/Region: IN - Requisition ID: 37467 - Work Model: - Position Type: - Salary Range: - Location: INDIA - NOIDA- BIRLASOFT OFFICE .
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