Walk-in || Azure Data Engineer

Job Description We are looking for an experienced Data Engineer with strong expertise in PySpark, Python, SQL, and Azure Databricks to design, develop, and optimize scalable data pipelines and big data solutions. Key Responsibilities Design, build, and maintain scalable data pipelines and data processing solutions. Work with large datasets using PySpark, Spark, and SQL . Develop and optimize data models for analytics and reporting. Implement batch and real-time data processing workflows. Collaborate with cross-functional teams to deliver high-quality data solutions. Perform performance tuning and optimization of Spark jobs and SQL queries. Ensure data quality, testing, and deployment best practices. Required Skills 5+ years of experience in Data Engineering or Big Data technologies. Strong hands-on experience in Python, PySpark, Spark, and SQL . Experience with Azure Databricks, Azure Data Lake, and Azure Data Factory . Knowledge of data modeling concepts and large-scale data processing. Experience building and optimizing ETL/ELT pipelines. Understanding of cloud-based data platforms and architectures. Nice to Have Experience with CI/CD pipelines and DevOps practices. Knowledge of GitLab, PowerShell, Shell/Bash scripting. Exposure to Power BI or other BI reporting tools. Experience working in Agile/Scrum environments. Financial domain experience is a plus. Keywords: Data Engineer, Big Data, PySpark, Spark, Python, SQL, Azure Databricks, Azure Data Factory, Azure Data Lake, ETL, Data Modeling, Cloud Data Engineering.