Job Requirements
About the Role
The Data Engineer GenAI within the Data & Analytics function will work closely with Data Scientists to support the development of generative AI solutions across text, audio, image, and tabular data domains. This role is responsible for managing large volumes of structured and unstructured data, ensuring its productive storage, retrieval, and augmentation to power GenAI models and applications. The ideal candidate will be skilled in building robust data pipelines, optimizing data architecture, and ensuring high standards of data reliability and governance.
Key Responsibilities
Primary Responsibilities
Build and maintain data engineering pipelines, with a focus on unstructured data.
Conduct requirements gathering and scoping sessions with business users and stakeholders to define GenAI-related data needs.
Design, build, and optimize data architecture and ETL pipelines for accessibility by Data Scientists and GenAI products.
Manage the full data lifecycle: ingestion, transformation, and consumption.
Ensure high standards of data reliability, integrity,



and governance.
Work with APIs to enable seamless data integration and usability.
Create technical design documentation for data pipelines and projects.
Debug technical issues and manage code versioning using Git.
Demonstrate experience with big data infrastructure such as MapReduce, Hive, HDFS, YARN, HBase, MongoDB, DynamoDB, etc.
Secondary Responsibilities
Apply machine learning and predictive analytics techniques where relevant.
Leverage domain knowledge in banking or financial services to enhance data solutions.
Present data insights using effective storytelling and visualization techniques.
What We Are Looking For
Education
Bachelor’s or master’s degree in computer science or Data Engineering or Information Systems or a related field.
Experience
2+ years of Proven experience in building and managing data pipelines and architectures.
Hands-on experience with big data technologies and cl

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