Data Engineer + ETL

As a Data Engineer (ETL) at our company, you will play a crucial role in designing, building, and maintaining scalable data pipelines and optimizing data processing frameworks. Your expertise in ETL/ELT development, cloud-based data platforms, and modern data engineering practices will be essential for enabling advanced analytics and AI-driven solutions across the organization. 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 preparing and engineering datasets for predictive analytics and LLM-based applications. - Ensure data quality, security, governance, and operational excellence across data platforms. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field. - 78 years of hands-on experience in Data Engineering and ETL/ELT development. - Strong expertise in Python, Spark, and SQL. - Experience working with Azure Databricks and Snowflake in enterprise environments. - Hands-on experience with Terraform and Infrastructure as Code (IaC). - Strong understanding of DevOps and CI/CD methodologies. - Experience with cloud-native services and distributed data processing systems. - Excellent analytical, troubleshooting, and communication skills. The company is looking for a highly skilled Data Engineer with expertise in ETL/ELT development, cloud-based data platforms, and modern data engineering practices. Hands-on experience with Azure Databricks, Snowflake, Spark, Python, and infrastructure automation is crucial for this role. Additionally, experience with AI/ML and Large Language Models (LLMs) will be a strong advantage. As a Data Engineer (ETL) at our company, you will play a crucial role in designing, building, and maintaining scalable data pipelines and optimizing data processing frameworks. Your expertise in ETL/ELT development, cloud-based data platforms, and modern data engineering practices will be essential for enabling advanced analytics and AI-driven solutions across the organization. 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 preparing and engineering datasets for predictive analytics and LLM-based applications. - Ensure data quality, security, governance, and operational excellence across data platforms. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field. - 78 years of hands-on experience in Data Engineering and ETL/ELT development. - Strong expertise in Python, Spark, and SQL. - Experience working with Azure Databricks and Snowflake in enterprise environments. - Hands-on experience with Terraform and Infrastructure as Code (IaC). - Strong understanding of DevOps and CI/CD methodologies. - Experience with cloud-native services and distributed data processing systems. - Excellent analytical, troubleshooting, and communication skills. The company is looking for a highly skilled Data Engineer with expertise in ETL/ELT development, cloud-based data platforms, and modern data engineering practices. Hands-on experience with Azure Databricks, Snowflake, Spark, Python, and infrastructure automation is crucial for this role. Additionally, experience with AI/ML and Large Language Models (LLMs) will be a strong advantage.