Data Engineer/FS-Engineer

Role Overview: You are a skilled Data Engineer / Full Stack Data Engineer with 8+ years of experience, proficient in PySpark, Databricks, Azure Data Factory (ADF), Big Data Ecosystems, Hadoop, and Hive. You will be joining a growing data engineering team and leveraging your expertise in distributed data processing and cloud data platforms, particularly within the Azure ecosystem. Key Responsibilities: - Design, build, and maintain scalable data pipelines using PySpark and Databricks. - Develop and orchestrate ETL workflows using Azure Data Factory (ADF). - Work on Big Data technologies including Hadoop and Hive for large-scale data processing. - Ensure performance optimization and tuning of data processes and jobs. - Collaborate with data scientists, analysts, and business stakeholders to deliver reliable data solutions. - Implement best practices in data engineering, including data quality, logging, monitoring, and alerting. - Troubleshoot and debug performance issues in data pipelines and environments. - Manage code in version control systems like Git and follow CI/CD practices. Qualification Required: - Strong hands-on experience with PySpark and Databricks. - Proficient in Azure Data Factory (ADF) and Azure cloud ecosystem. - In-depth knowledge of Big Data technologies like Hadoop, Hive. - Experience with data modeling, data warehousing, and building large-scale data systems. - Strong understanding of data governance, data quality, and security best practices. - Good knowledge of SQL and performance tuning in large data sets. - Familiarity with Git, DevOps pipelines, and agile methodologies. Additional Details: You must be willing to go to the client location to collect the laptop. (Note: Company-specific details are not available in the provided job description.),