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We are seeking an experienced Data Engineering / Data Infrastructure Team Lead to guide a high-performing team in designing, scaling, and managing the robust, cost-efficient infrastructure powering our solution.
In this role, you will balance technical excellence with people leadership. You will architect distributed data systems and cloud-native technologies to safeguard our clients' revenue while driving strategic initiatives that align with business objectives, operational efficiency, and team growth.
Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.
Your Arena:
Leadership & Mentorship: Lead, mentor, and scale a team of talented data and infrastructure engineers. Cultivate a culture of technical excellence, continuous learning, and psychological safety.
Data Infrastructure & FinOps: Own the architecture and evolution of our modern data stack, ensuring robust, scalable backend services while driving cloud cost management (FinOps) to maximize resource efficiency.
High-Performance Engineering: Oversee the design of distributed systems, real-time streaming, and batch pipelines capable of processing millions of daily transactions with minimal latency.
Operational Excellence: Champion Infrastructure-as-Code (IaC), rigorous security compliance, data governance, and deep observability (monitoring/alerting) across the R&D organization.
Strategic Collaboration: Act as the bridge between data engineering, product, data science, and core R&D teams to execute complex cross-functional initiatives.

We are seeking our Data Operations Team Leader!
This person will oversee a team of data operations specialists responsible for labeling data for machine learning and AI projects.
This role involves managing day-to-day operations, ensuring annotation quality and accuracy, developing guidelines, and collaborating with cross-functional teams to meet project deadlines and objectives.
What Youll Do:
Manage the end-to-end data workflow, from incoming data through annotation delivery to the ML teams, including overseeing data upload processes and ensuring data availability.
Manage database operations and ensure the integrity and availability of annotation data.
Become a Subject Matter Expert in our data and actively participate in hands-on annotation projects.
Create and maintain onboarding materials, annotation guidelines, and operational documentation to support knowledge sharing and consistent annotation practices.
Lead a team of Data Operations Specialists by managing task assignments, scheduling, and day-to-day execution. Provide the tools and processes needed for efficient work, ensure high annotation quality in collaboration with the ML teams, and continuously improve workflow efficiency
Own the annotation platform, driving bug fixes, feature development, and workflow improvements using Python and GenAI tools.
Develop and maintain operational dashboards and real-time performance metrics to monitor team efficiency, quality, and output.
Collaborate closely with data scientists, machine learning engineers, and product managers to understand annotation requirements and project goals. Coordinate cross-functional communication, monitor operational KPIs, and oversee daily operations to keep projects on track and ensure adherence to shifting schedules.

We are seeking an experienced Data Science Team Lead to lead our data science and data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products.

You will lead the team through architecture decisions, development, and deployment of mission-critical systems-while growing and mentoring a high-performing team.

Responsibilities

Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure.
Design, build, and maintain distributed data processing workflows (batch & streaming).
Drive best practices for data quality, validation, testing, and observability.
Own and evolve data architecture in alignment with business and product goals.
Manage sprint planning, task breakdown, code reviews, and performance feedback for your team.
Contribute hands-on to key development tasks and architecture decisions.
Recruit, mentor, and grow the data science engineering team.

we are looking for a BI Team Lead.
The successful BI Team lead, will play a key role in managing and growing a team responsible for delivering impactful data products and solutions.
As a BI Team Lead, you will oversee the personal and professional development of your team, while also being the main point of contact for client-facing data initiatives. Youll drive data strategy and contribute to new initiatives that support cross-company objectives. This role involves collaborating with product managers, business stakeholders, and leadership to design, develop, and maintain scalable analytics solutions. You will also enhance the companys understanding of key business metrics by building automated tools and insightful visualizations in a rich data environment.
You will also be responsible for integrating AI and machine-learning capabilities into BI solutions, including developing automation processes and AI agents to support decision-making.

Were looking for a Data & Analytics Team Lead to manage and grow our data team and own the data layer behind our AI. Youll lead a team of data analysts responsible for neural-network model analysis, model performance tracking, customer-facing and internal BI. Youll act as both the people manager and the technical lead for the team, setting technical direction while staying hands-on.

Youll thrive in this role if youre passionate about turning data into better AI products, enjoy solving complex analytical problems, and like working at the intersection of Data, Analytics, and Artificial Intelligence.

Responsibilities:

Lead the data strategy supporting AI model development, evaluation, and continuous improvement
Define KPIs and monitoring frameworks for AI model performance.
Analyze NN model outputs, build and maintain model-tracking and performance-evaluation workflows
Drive close calibration with the Algo, Product, and Data Engineering teams to align data definitions, pipelines, and metrics
Stay hands-on with SQL, Python, BI tooling, and the modern data stack
Build and own agentic data workflows - designing the context, tooling, and data access that let AI agents reliably query, analyze, and act on company data

We are looking for an experienced Data Infrastructure Team Lead to lead our Data Infrastructure team. In this role, you will have formal people-management responsibility for a multidisciplinary team that builds, productionizes, and improves big data and analytics infrastructure. You will be responsible for team delivery, combining technical depth, agile leadership, and an AI-first mindset to help the team build reliable systems, improve how it works, and continuously raise its engineering standards.

Location: Ramat Gan (Bursa area), Israel - Hybrid model

What will you do?

Lead, manage, and develop a data infrastructure team of approximately 5-7 people.
Take responsibility for team delivery, including planning, prioritization, execution, and continuous improvement.
Lead agile ways of working, including scrum-based delivery practices.
Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure.
Partner closely with cross-functional stakeholders across technical, scientific, and business interfaces.
Help the team adopt AI-first engineering practices, including automation and AI-assisted development workflows.
Drive improvements in team processes, technical quality, delivery predictability, and collaboration.
Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems.
Create an environment where team members can grow, contribute, and improve together.