Description

You will build and maintain scalable data infrastructure to support core business functions.

This role is hybrid.

Responsibilities

• Design and maintain scalable data pipelines using Snowflake, PySpark, and SQL.
• Write optimized SQL queries for data extraction, transformation, and loading (ETL/ELT).
• Develop data models and schemas aligned with banking domain requirements.
• Automate data workflows to ensure data quality, accuracy, and integrity.
• Manage release processes, deployment, and version control for data pipelines.

Required Skills

• Proven experience as a Data Engineer with Snowflake, Python, PySpark, and SQL.
• Strong understanding of ETL/ELT processes and data warehousing concepts.
• Hands-on experience with release management, deployment, and version control.
• Proficiency in Python scripting and PySpark for data processing.
• Knowledge of Data Governance, security, and privacy standards.
• Familiarity with CI/CD Pipelines.
• Understanding of banking and financial services industry data and compliance.

Preferred Skills

• Good knowledge of Azure and Databricks.
• Knowledge of Apache Kafka or other streaming technologies.

Key Skills

Education

Not specified