Description

Job Responsibilities include:

Design, develop, and maintain scalable data pipelines and cloud-based data solutions using Azure Databricks, Azure Data Factory, ADLS, and Synapse Analytics.

Lead data migration initiatives from on-premises databases to Azure cloud platforms while ensuring data quality, integrity, and performance.

Develop and optimize data processing frameworks using Python, SQL, Databricks, DataFrames, and distributed data processing technologies.

Build and manage Azure Databricks services, including data ingestion, transformation, storage, and integration with Azure and Snowflake platforms.

Collaborate with business, analytics, and technology teams to deliver data solutions that support banking and enterprise reporting requirements.

Troubleshoot performance issues, optimize data workflows, and implement best practices for cloud data engineering, scalability, and operational efficiency.

Required Qualifications:

Bachelor’s degree in computer science, Information Technology, Data Engineering, Software Engineering, or a related technical field.

10+ years of experience in Data Engineering, Cloud Data Platforms, and Enterprise Data Management, preferably within the Banking or Financial Services domain.

Strong expertise in Azure Databricks, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure Synapse Analytics, SQL, and Python for large-scale data engineering solutions.

Proven experience building data pipelines, migrating on-premises data to Azure Cloud, working with Databricks (DBFS, DataFrames, RDDs), and integrating data with Snowflake and Azure-based data platforms

Key Skills

Education

Any Graduate