Job Description
Reporting to Manager,Data Science,the role holders will build and maintain reliable data infrastructure and pipelines; ensure that the Bank’s data is accurate, complete, consistent and well documented; implement data governance policies, standards and stewardship arrangements; and lead the Bank’s adoption of artificial intelligence by designing, building and deploying AI solutions, including large language model (LLM), generative AI and agentic AI applications, that automate processes, enhance analysis and support policy and research.
Job Responsibilities
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Develop applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning techniques to deliver accurate, context-aware responses grounded in institutional data.
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Assess and continuously improve AI solutions in terms of accuracy, reliability, performance, scalability, and cost-effectiveness, while minimizing hallucinations and unintended outcomes.
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Collaborate closely with data scientists, AI engineers, data quality analysts, and other stakeholders to translate business requirements into effective data systems.
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Design, develop, and maintain robust, scalable ETL/ELT pipelines for integrating and transforming data from multiple sources, and develop secure APIs to serve governed, analytics-ready datasets to downstream analytical platforms, business intelligence solutions, and AI/ML applications.
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Build, manage, and optimize transactional (OLTP) and analytical (OLAP) databases, preferably PostgreSQL and ClickHouse, ensuring performance, security, scalability, and reliability.
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Document data engineering processes, pipelines, and solutions to ensure that all workflows are understood, reproducible, and maintainable.
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Perform data cleaning, validation, and profiling to enforce business rules and ensure data accuracy, consistency, completeness, and integrity.
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Gather, and document business requirements from technical and non-technical stakeholders, translating them into well defined data quality rules and validation checks.
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Develop, implement, and monitor data pipelines that integrate data quality checks, following data engineering best practices to ensure reliable data quality.
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Apply data governance principles, policies, standards, and procedures in implementing the data quality program.
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Assist in developing and documenting data governance policies, standards, and procedures in line with recognized frameworks such as DAMA-DMBOK.
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Implement data catalogue, business glossary, and data lineage mapping for the Bank’s Data Warehouse (EDWH).
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Collaborate with stakeholders across the Bank to ensure adherence to data governance practices.
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Support the Bank’s data governance culture by contributing to existing knowledge-sharing and awareness initiatives and helping develop new ones
Job Requirements
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Master’s degree in computer science, data science, software development, information Technology, or a related field.
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35years
Female candidates are encouraged to apply
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