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.
(ref : hirist.tech)
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Data Engineer Python • Pune
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