As an AI Data Engineer, you'll create and manage data pipelines that support AI initiatives in a financial tech environment. This role is ideal for someone with a strong background in data engineering and a passion for AI.
In this role as an AI Data Engineer, you will be responsible for creating AI-ready datasets that empower data scientists and AI engineers. Your main task will be to design and build data pipelines that are not only efficient but also scalable and secure. You will work closely with various teams, including AI Platform Engineering and MLOps, to ensure that the data products you develop meet the needs of advanced analytics and machine learning applications.
Your day-to-day responsibilities will involve collaborating with stakeholders to understand their data needs and translating those into robust data engineering solutions. You will also ensure that the data platforms you create adhere to enterprise governance and privacy standards, which is crucial in the financial technology sector. This role requires a strong understanding of both real-time and batch processing to support diverse data requirements.
The ideal candidate for this position will have a solid background in data engineering, with at least three years of experience in the field. You should be comfortable working in a fast-paced environment and have a passion for leveraging data to drive AI innovation. Familiarity with financial technology and MLOps practices will be advantageous, but the key requirement is your ability to deliver high-quality data solutions that support business objectives.
If you are looking to make an impact in a dynamic team focused on cutting-edge AI solutions, this role could be a great fit for you. Your expertise will play a vital role in enabling production-ready AI, making this an exciting opportunity for those who thrive in a collaborative and innovative setting.
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