Data Engineer

Role overview

Skills and experience

• At least five years of commercial experience in a data-driven role, including hands-on data mart and ETL pipeline development.
• Expert Python ETL scripting and ability to write clean, maintainable, robust code.
• Experience with end-to-end SDLC, UAT, UAT bug fixes, production deployment, and post-production support.
• Expertise in Oracle queries and data analysis, and PySpark debugging.
• Knowledge of software engineering concepts, production pipelines, and data warehousing.
• Ability to work across structured, semi-structured, and unstructured data.
• Hands-on experience with Python, Spark/PySpark, Hadoop/MapReduce, Hive, and Pandas.
• Familiarity with query languages, SQL and NoSQL databases, CI/CD, testing, and data validation.
• Banking client or banking domain knowledge is referenced.

Work environment

• The employer describes a virtual-first work environment with flexibility.

Company information and benefits

• The company describes itself as having more than 219,000 employees across 54 countries.
• The employer highlights a diverse workforce, comprehensive benefits, and a positive work environment.

Responsibilities

• Build data marts and ETL pipelines using Python and PySpark.
• Write and maintain robust Python ETL scripts and production data pipelines.
• Analyze data and work with Oracle queries and structured, semi-structured, and unstructured data.
• Debug PySpark code and ensure production pipeline quality.
• Support end-to-end SDLC activities, including UAT, bug fixes, deployment, and post-production support.
• Perform data testing and validation and work with CI/CD processes.
• Work with data warehousing technologies and banking client data.