What you'll do:

• Design, develop, and maintain scalable data pipelines that support the ingestion and processing of large datasets for AI/ML applications.
• Collaborate with data scientists and business stakeholders to identify and define AI/ML use cases that drive value.
• Clean, preprocess, and transform raw data into structured formats suitable for analysis and machine learning tasks.
• Work closely with data scientists to ensure data is optimized for AI/ML use cases.
• Ensure data quality, integrity, and availability for AI/ML initiatives.
• Conduct exploratory data analysis to inform model development and feature engineering.
• Optimize machine learning models for performance and scalability, utilizing best practices in model evaluation and selection.
• Monitor data pipelines and AI/ML processes to ensure reliability and performance.
• Troubleshoot and resolve data-related issues, ensuring data integrity throughout the pipeline.

What makes you a great fit:

• 6+ years of experience as a Data Engineer, with a strong focus on AI/ML applications.
• Proficiency in Python for data manipulation and processing.
• Experience with data pipeline tools (e., Apache Airflow, Luigi, or similar).
• Solid understanding of data architecture, data modelling, and ETL processes.
• Familiarity with cloud platforms (e., AWS, Azure, GCP) and containerization technologies (e. , Docker, Kubernetes) is a plus.
• Experience in the banking or fintech industry is highly desirable.
• Knowledge of SQL and NoSQL databases for data querying and management.
• Familiarity with machine learning frameworks (e., TensorFlow, PyTorch) is a plus, but not required