Senior Data Engineer

Based in Islamabad, this role focuses on enhancing the data science and engineering team by introducing new tooling and automation solutions. The primary objective is to make institutional knowledge more accessible and usable across the organization. The position requires a blend of practical experience with Retrieval-Augmented Generation (RAG) and large language models (LLMs), alongside strong data engineering skills. Collaboration with team members is essential to pilot innovative tools and automate workflows, while also contributing directly to core data pipeline engineering and streamlining manual monitoring and alert processes. The role also explores opportunities to improve cross-departmental collaboration within the bank.

Key Responsibilities

- Lead the identification and development of AI and automation use cases to improve existing workflows in data engineering, code reviews, and knowledge retrieval.
- Build and implement tooling solutions, including those based on LLM and RAG technologies, to operationalize these use cases effectively.
- Enhance the organization’s knowledge base by driving measurable improvements in coverage and accuracy.
- Coordinate knowledge-transfer sessions with subject-matter experts to capture critical logic that may not be documented in code.
- Collaborate closely with other teams to pilot new tools and support the rollout of successful automation initiatives.
- Contribute hands-on to the engineering of core data pipelines and automate manual monitoring and alert workflows to increase efficiency.

Required Qualifications

- 4 to 7 years of experience in data or software engineering, with practical expertise in LLM/RAG tooling and automation scripting.
- Proficiency in Git-based workflows and version control.
- Strong background in reverse-engineering undocumented legacy code is highly desirable.
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.

This role offers the opportunity to work at the forefront of AI-driven automation within a dynamic banking environment, contributing directly to the modernization of data engineering practices and knowledge management.