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Immediate Joiner Job Title: Data Engineer Location: Noida, Film City Sector 16A Experience: 3.5-7 years Budget: Upto 40LPA Role: We are looking for a highly skilled Data Engineer to design, build, and operate scalable enterprise data platforms on Azure. The ideal candidate will have strong expertise in Databricks, Spark/PySpark, Azure Data Factory, ADLS Gen2, Python, SQL, and modern lakehouse architecture, enabling reliable, high-quality data solutions that power analytics, AI, and business decision-making across the organization. Key Responsibilities: Data Platform Engineering Design and develop scalable data pipelines using Azure Data Factory, Databricks, and Spark/PySpark Build and maintain enterprise-grade lakehouse solutions using Delta Lake and Medallion Architecture (Bronze, Silver, Gold) Data Integration & Transformation Develop ingestion, transformation, validation, and publishing frameworks for structured and semi-structured data Implement efficient ETL/ELT processes using Python and SQL Data Modeling & Architecture Design conceptual, logical, and physical data models for lakehouse, warehouse, and analytics platforms Translate business requirements into scalable and performant data structures Data Quality & Governance Implement data quality checks, validation, reconciliation, and monitoring processes Support metadata management, lineage, governance, and security best practices Performance & Optimization Optimize Spark workloads, partitioning strategies, Delta tables, and pipeline performance Ensure scalability, reliability, and operational excellence of data platforms DevOps & Operations Support CI/CD, environment promotion, monitoring, logging, and production operations Collaborate with engineering and analytics teams to deliver robust data solutions Required Experience: 57 years of experience in Data Engineering, Data Warehousing, or Data Platform Engineering IN INSURANCE domain. Insurance knowledge is must. Strong hands-on experience with: Azure Cloud Azure Data Factory (ADF) ADLS Gen2 Databricks (Unity Catalog) Apache Spark / PySpark Python SQL Delta Lake and Lakehouse Architecture Experience designing enterprise data models and data transformation solutions Strong understanding of data quality, validation, reconciliation, and operational support Experience with Git and CI/CD practices Preferred Experience: Apache Airflow or similar orchestration tools Kafka and streaming data pipelines Docker and Kubernetes Azure Synapse Analytics Microsoft Fabric Data lineage, observability, and governance tools Terraform or Infrastructure-as-Code Python API development Why this role stands out: Opportunity to build and scale a modern Azure lakehouse platform Direct impact on enterprise analytics, AI, and digital transformation initiatives Exposure to cutting-edge cloud, data engineering, and platform technologies Work on complex, high-volume data challenges in a fast-growing P&C insurance environment Immediate Joiner Job Title: Data Engineer Location: Noida, Film City Sector 16A Experience: 3.5-7 years Budget: Upto 40LPA Role: We are looking for a highly skilled Data Engineer to design, build, and operate scalable enterprise data platforms on Azure. The ideal candidate will have strong expertise in Databricks, Spark/PySpark, Azure Data Factory, ADLS Gen2, Python, SQL, and modern lakehouse architecture, enabling reliable, high-quality data solutions that power analytics, AI, and business decision-making across the organization. Key Responsibilities: Data Platform Engineering Design and develop scalable data pipelines using Azure Data Factory, Databricks, and Spark/PySpark Build and maintain enterprise-grade lakehouse solutions using Delta Lake and Medallion Architecture (Bronze, Silver, Gold) Data Integration & Transformation Develop ingestion, transformation, validation, and publishing frameworks for structured and semi-structured data Implement efficient ETL/ELT processes using Python and SQL Data Modeling & Architecture Design conceptual, logical, and physical data models for lakehouse, warehouse, and analytics platforms Translate business requirements into scalable and performant data structures Data Quality & Governance Implement data quality checks, validation, reconciliation, and monitoring processes Support metadata management, lineage, governance, and security best practices Performance & Optimization Optimize Spark workloads, partitioning strategies, Delta tables, and pipeline performance Ensure scalability, reliability, and operational excellence of data platforms DevOps & Operations Support CI/CD, environment promotion, monitoring, logging, and production operations Collaborate with engineering and analytics teams to deliver robust data solutions Required Experience: 57 years of experience in Data Engineering, Data Warehousing, or Data Platform Engineering IN INSURANCE domain. Insurance knowledge is must. Strong hands-on experience with: Azure Cloud Azure Data Factory (ADF) ADLS Gen
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