About us
Sharegain began with one question: If the largest institutions solely exercise the right to lend their stocks, bonds, and ETFs, what would it take to unlock this revenue opportunity for every investor?
Our team of experts in the UK, US and Israel built the solution: a platform that empowers online brokers, private banks, and wealth managers to offer securities lending to their clients. We call it SLaaS: Securities Lending as a Service. It’s a fully digital, customizable, end-to-end solution that automates front- and back-office operations. Institutions and investors are now free to earn more from what they own.
Every Sharegainer has their own backstory, but we all share an ambition to do things differently – bigger, better, and greater. Together we’re on a mission to democratize capital markets by building a more liquid world. The more we share, the more we all gain.
About the role
Sharegain is looking for an experienced and driven Data Team Lead to join our R&D organization. In this role, you will lead a team of data engineers while taking hands-on ownership of data infrastructure, pipelines, and quality standards. You will play a key role in shaping how data is built, used, and trusted across the company - from our core platform through to analytics and AI-native applications.
This is both a technical leadership and people management role. You will mentor the team, drive execution, collaborate cross-functionally, and contribute to the evolution of our data platform and Data Center monitoring solutions.
Responsibilities:
Team Leadership
Lead, mentor, and grow a team of data engineers, fostering a culture of quality, ownership, and continuous improvement.
Drive prioritization of team initiatives, balancing technical debt, new capabilities, and stakeholder requests.
Data Engineering & Architecture
Define and drive the data architecture strategy, including the design of scalable pipelines, ETL workflows, and Data Lake expansion.
Collaboration & Enablement
Partner closely with R&D, architecture, and business teams to understand data needs and translate them into robust, scalable solutions.
Lead the team in designing, optimizing, and evaluating AI prompts and data-driven applications; drive structured experimentation across models, prompts, and architectures.
Requirements:
