תיאור המשרה
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.
Serve as a key subject matter expert for data pipelines, governance, and analytics within the team’s scope.
Data Engineering & Architecture
Define and drive the data architecture strategy, including the design of scalable pipelines, ETL workflows, and Data Lake expansion.
Oversee the design and maintenance of schemas, data structures, and data organization standards.
Own data quality, integrity, and validation standards across the organization.
Collaboration & Enablement
Partner closely with R&D, architecture, and business teams to understand data needs and translate them into robust, scalable solutions.
Promote data-driven practices across teams, providing guidance and technical enablement.
Work effectively across distributed, international R&D teams.
AI & Data Applications
Lead the team in designing, optimizing, and evaluating AI prompts and data-driven applications; drive structured experimentation across models, prompts, and architectures.
Take ownership of the team’s AI and data features - from design through implementation and production including AI-native capabilities such as autonomous agents and intelligent data workflows.
Requirements:
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
5 years of hands-on experience in Data Engineering, with at least 2 years in a team lead or technical leadership role.
Proven ability to lead and develop technical teams in a fast-paced environment.
Deep expertise in SQL and advanced analytics.
Strong understanding of data and schema standards, data modeling, and governance concepts.
Deep familiarity with Databricks.
Hands-on familiarity with the Azure cloud platform and cloud-native development practices.
Demonstrated experience designing and delivering robust ETL pipelines and data integration frameworks.
Excellent analytical thinking combined with the ability to communicate complex ideas clearly to technical and non-technical stakeholders.
Strong system-level problem-solving skills with the ability to make architectural trade-offs.
Experience with modern analytics tools and platforms such as Spark, data lakes, and similar.
Hands-on experience with LLMs, AI prompt design, and building production-grade AI applications.
Advantage:
Previous experience as a DBA.
Experience with NoSQL databases.
Ability to prototype and validate ideas quickly through Proof of Concepts.
