Data Team Leader (Fintech)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Data Team Leader (Azure/Databricks): Leading a team of data engineers to build and optimize data infrastructure, pipelines, and quality standards for a securities lending platform with an accent on scalability and AI integration. Focus on designing robust ETL workflows, managing Data Lake expansion, and implementing production-grade AI-native capabilities.
Location: Hybrid (Netanya, Israel)
Company
provides a digital, end-to-end SLaaS (Securities Lending as a Service) platform that enables brokers and banks to offer securities lending to their clients.
What you will do
- Lead, mentor, and grow a team of data engineers, fostering a culture of quality and ownership.
- Define and drive data architecture strategy, including scalable pipelines, ETL workflows, and Data Lake expansion.
- Own data quality, integrity, and validation standards across the organization.
- Partner with R&D and business teams to translate data needs into robust, scalable solutions.
- Design and optimize AI prompts and production-grade AI-native applications, including autonomous agents.
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.
- Deep expertise in SQL, advanced analytics, and data modeling/governance.
- Strong proficiency with Databricks and the Azure cloud platform.
- Experience designing and delivering robust ETL pipelines and data integration frameworks.
- Hands-on experience with LLMs, AI prompt design, and building AI applications.
Nice to have
- Previous experience as a DBA.
- Experience with NoSQL databases.
- Ability to quickly prototype and validate ideas through Proof of Concepts.
Будьте осторожны: если работодатель просит войти в их систему, используя iCloud/Google, прислать код/пароль, запустить код/ПО, не делайте этого - это мошенники. Обязательно жмите "Пожаловаться" или пишите в поддержку. Подробнее в гайде →