About this role
The team is seeking a hands-on Data Engineer with strong expertise in PySpark and Python to build and maintain data marts and ETL pipelines within a banking environment. The ideal candidate will own the full Software Development Life Cycle (SDLC), from build through User Acceptance Testing (UAT), bug fixing, production deployment, and post-production support.
Key Responsibilities:
- Design, build, and maintain ETL pipelines and data marts using PySpark and Python.
- Write clean, maintainable, and robust production-grade code.
- Own end-to-end SDLC activities, ensuring high-quality deliverables.
- Collaborate with cross-functional teams to gather requirements and implement solutions.
- Monitor and optimize ETL processes for performance and reliability.
- Troubleshoot and resolve issues in production environments.
Required Skills & Qualifications:
- Strong experience with PySpark and Python programming.
- Proficiency in ETL processes and data warehousing concepts.
- Familiarity with banking domain data requirements and compliance standards.
- Experience with version control systems, such as Git.
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
Experience:
- 5-8 years of relevant experience in data engineering or a similar role.
What we offer:
- Opportunity to work in a dynamic and challenging environment.
- Professional growth and development opportunities.
- Collaborative team culture and innovative projects.
Applications are read by our talent team, usually within two working days.
If you look like a fit we will call you, and you will hear from us either way.