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About the role
Experience: 10+ YearsLocation: Kochi / Coimbatore / Chennai / Mumbai / PuneLinkedIn Profile: MandatoryAbout the Role:We are looking for an experienced Lead Data Engineer to design, develop, and support enterprise-grade data platforms and pipelines. The ideal candidate should have strong expertise in Azure Data Engineering, Databricks/Microsoft Fabric, PySpark, SQL, data migration, and modern data architecture, along with hands-on experience in production and L2/L3 support.Key Responsibilities:- Design and develop scalable enterprise data pipelines using Azure data technologies.- Build and optimize data solutions using Azure Data Factory, Azure Databricks/Microsoft Fabric, PySpark, and Delta Lake.- Implement Medallion Architecture and modern data engineering best practices.- Lead data migration initiatives and ensure data quality, reliability, and performance.- Develop effective data models and optimize complex SQL queries and data workloads.- Perform performance tuning, job monitoring, troubleshooting, and failure recovery.- Provide L2/L3 production support, including RCA, incident resolution, and job failure troubleshooting.- Participate in on-call support and Hypercare activities during critical releases and migrations.- Ensure data governance, security, documentation, and compliance standards.- Mentor data engineers and provide technical guidance across projects.Mandatory Skills:- Advanced SQL- Azure Data Factory (ADF)- Azure Databricks / Microsoft Fabric- PySpark- Delta Lake- Medallion Architecture- Data Migration- Data Modeling- Production Support / L2-L3 Support- RCA & Job Failure Troubleshooting- On-call Support & HypercareQualification:- Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or a related field.Ideal Candidate:- 10+ years of experience in Data Engineering with strong Azure expertise.- Proven experience handling enterprise-scale data platforms and production environments.- Strong problem-solving, troubleshooting, communication, and mentoring skills. (ref:hirist.tech) .
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