Opening For Data engineer(preferred banking doamin)

Job highlights

• 8+ years in BI/DW with Azure data platform expertise, strong Python and PySpark skills, knowledge of banking data models and regulatory compliance

• Design, develop, and maintain scalable data pipelines using Azure Data Factory, Databricks, Synapse, and Azure Data Lake; perform data analysis and transformation; integrate legacy banking data; mentor junior engineers

• Design, develop, and maintain scalable data pipelines using Python and modern data engineering tools.

• Understanding of banking data models, financial reporting, and regulatory compliance.

• Integrate data from legacy banking platforms into modern data lakes and warehouses.

• Collaborate with business analysts, architects, and operations teams to understand core banking workflows and data requirements.

• Design, build, and maintain scalable and reliable data pipelines using Azure Data Factory, Databricks, Synapse (Azure SQL DW), and Azure Data Lake.

• Perform data analysis and transformation using PySpark on Azure Databricks or Apache Spark.

• Design and implement data models optimized for storage and various query patterns.

• Work with structured, semi-structured, and unstructured data.

• Utilize various database technologies including Traditional RDBMS, MPP, and NoSQL.

• Ensure compliant handling and management of data.

• Experience in building end-to-end data pipelines in a cloud environment.

• Mentor junior engineers and contribute to the development of best practices and reusable frameworks.

Skills Expected:

• 8+ years of relevant IT experience in the BI/DW domain with hands-on experience on the Azure modern data platform.
• Strong knowledge and experience with the Python programming language
• Experience using version control systems like Git, bitbucket.
• Experience in data analysis and transformation using PySpark on Azure Databricks or Apache Spark.
• Good knowledge of Distributed Processing using Databricks or Apache Spark.
• Experience in creating data structures optimized for storage and various query patterns.
• Experience of integrating Unity Data Catalog with the Databricks and registering data assets etc.
• Understanding of CI/CD pipelines.
• Knowledge of Agile/Scrum methodologies.