Senior Data Engineer - Global Liquid Markets (Public Markets)

As a Senior Data Engineer within the Public Markets squad, you will be a hands-on contributor, collaborating closely with your Product Owner, Tech Lead, fellow engineers, and business stakeholders to deliver high-quality data solutions. Build data people can trust: Design and run automated, high-performance data pipelines on Snowflake and AWS that bring market and vendor data into the platform reliably and at scale. Build the data products: Develop and enhance data models behind scalable products that power analytics and applications used in real investment decisions with an AI-first mindset. Make quality a standard, not an afterthought: Implement testing practices, from unit tests built into the pipeline to independent regression testing, following shared quality standards with Core Data and data governance. Apply AI-powered data engineering: Use AI to speed up how the squad builds, tests, and operates data pipelines, and apply agentic AI to automate repetitive engineering work, with sound guardrails and human review. Collaborate with product and business partners: Partner with the Product Owner, Tech Lead, and stakeholders to understand business needs, refine requirements, and contribute to a prioritized data roadmap. Contribute to engineering excellence: Mentor engineers, participate in code reviews, share knowledge, and follow engineering best practices to continuously improve squad delivery and quality. Bachelor or Master`s degree in technical or business discipline or equivalent experience Generally 5+ years of professional experience Highly proficient in data engineering languages and tools, and strong proficiency in general programming languages and frameworks; ability to develop on multiple platforms Strong negotiation, facilitation and consensus building skills Strong oral and written communication skills; presentation skills Extensive knowledge of the following: IT concepts, strategies, methodologies Versed in diverse technologies and new technical architecture principles and concepts Extensive knowledge in layered systems architectures solutions and designs and shared data engineering concepts Business function(s) and I/T industry business issues; extensive knowledge of business operations, strategies and objectives Extensive understanding of agile data engineering concepts and processes Must be proactive, demonstrate initiative and be a logical thinker Extensive consultative skills, including the ability to understand and apply customer requirements, including drawing out unforeseen implications and making recommendations for design, the ability to define design reasoning, understanding potential impacts of design requirements Extensive understanding of backlog tracking, burndown metrics, and incremental delivery Experience using AI tools to improve the speed, quality, and scale of work; can point to concrete workflows where AI adds value; critically evaluates and validates AI-generated output; and applies AI responsibly, protecting confidential and customer data. Strong collaboration, prioritization, and adaptability skills required