Azure Data Engineers with Synapse, Databricks

2 days ago


Kolkata Mumbai Pune, India Zensar Technologies Limited Full time

Job Description Description We are seeking an experienced Azure Data Engineer with expertise in Azure Synapse and Databricks to join our dynamic team. The ideal candidate will have 3-6 years of experience in designing and implementing data solutions in the Azure ecosystem. You will play a crucial role in building scalable data pipelines, collaborating with cross-functional teams, and ensuring data quality and compliance. If you are passionate about data engineering and have the skills to drive impactful data solutions, we would love to hear from you. Responsibilities - Design, develop, and maintain scalable data pipelines using Azure Synapse and Databricks. - Collaborate with data scientists and analysts to understand data needs and deliver reliable data solutions. - Implement data modeling techniques to optimize data storage and retrieval in Azure. - Monitor and troubleshoot data pipeline performance and implement improvements as needed. - Ensure data security and compliance with industry standards and regulations. - Perform data cleansing and transformation to prepare data for analysis. - Document processes and maintain metadata repositories for data pipelines. Skills and Qualifications - Bachelor's degree in Computer Science, Engineering, or a related field. - 3-6 years of experience working with Azure Data services, specifically Azure Synapse and Databricks. - Strong proficiency in SQL and experience with data warehousing concepts. - Experience with ETL processes and data integration tools. - Familiarity with big data technologies such as Apache Spark. - Knowledge of data modeling techniques and data architecture best practices. - Experience in programming languages such as Python or Scala. - Understanding of Azure DevOps for CI/CD pipeline implementation. - Strong problem-solving skills and ability to work in a fast-paced environment. - Good communication skills and ability to work collaboratively in a team.


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