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Data Engineer (ETL) Azure Databricks | Snowflake | PySparkJob Title Data Engineer (ETL) Experience Required 78 Years Work Model Hybrid (Pan India) Work Timings 11:00 AM 9:00 PM IST Job Summary We are looking for a highly skilled Data Engineer with strong expertise in ETL/ELT development, cloud-based data platforms, and modern data engineering practices. The ideal candidate will have hands-on experience with Azure Databricks, Snowflake, Spark, Python, and infrastructure automation. Experience working with AI/ML and Large Language Models (LLMs) will be a robust advantage. The candidate will be responsible for designing, building, and maintaining scalable data pipelines, optimizing data processing frameworks, and enabling advanced analytics and AI-driven solutions across the organization. Required Skills - Data Engineering and ETL/ELT Processes - Python - Apache Spark (PySpark, Spark SQL) - Azure Databricks (Unity Catalog) - Snowflake - Azure Functions - Azure Service Bus - SQL - Terraform - CI/CD Tools and Processes - GitHub Actions - Git - Artifactory - SonarQube - AI/ML and Large Language Models (LLM) Key Responsibilities - Design, develop, and maintain scalable ETL/ELT pipelines for enterprise data platforms. - Build and optimize data processing solutions using Python, PySpark, and Spark SQL. - Develop and manage data solutions on Azure Databricks and Snowflake. - Implement and maintain Unity Catalog-based governance and security frameworks. - Create serverless integrations and event-driven workflows using Azure Functions and Azure Service Bus. - Develop efficient SQL queries, data models, and performance optimization strategies. - Automate infrastructure deployment and management using Terraform. - Implement CI/CD pipelines and DevOps best practices using GitHub Actions, Git, Artifactory, and SonarQube. - Collaborate with data architects, business analysts, and cross-functional teams to deliver data-driven solutions. - Support AI/ML initiatives by .
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