Key Responsibilities:

• Design, build, and maintain scalable ETL pipelines using Azure Data Factory and Snowflake.

• Develop and optimize complex SQL queries for data extraction, transformation, and loading.

• Collaborate with business analysts, and stakeholders to understand data requirements and deliver robust solutions.

• Ensure data quality, integrity, and security in compliance with banking regulations.

• Monitor, troubleshoot, and enhance data workflows for performance and reliability.

• Document data processes, data flows, and technical specifications.

• Architect and implement data lake solutions to support structured and unstructured data.

Required Skills & Experience:

• Bachelor’s or master’s degree in computer science, Engineering, or related field.

• 5+ years of experience as a Data Engineer, preferably in the banking or financial services industry.

• Advanced proficiency in SQL and experience with Snowflake data warehousing.

• Hands-on experience with Azure Data Factory and Azure Data Lake.

• Strong understanding of ETL concepts, data modeling, and data integration best practices.

• Experience working with large-scale data sets and real-time data processing.

• Familiarity with data governance, security, and compliance in regulated environments.

• Excellent problem-solving, communication, and collaboration skill.

Good to have:

• Experience with additional Azure services.

• Knowledge of Python or other scripting languages for data engineering tasks.

• Understanding of banking data domains such as payments, risk, or regulatory reporting.