Data & AI Group Manager - 242294

We are seeking an experienced and visionary Data & AI Group Manager to lead and scale our Data & AI organization. This is a high-impact leadership role with end-to-end ownership of the company's Data & AI strategy, execution, delivery, and business outcomes.

📍Our offices are currently located in Tel Aviv and will relocate to Herzliya in December

In this role you will lead Data Engineering managers, senior technical leaders, and engineering teams while defining the long-term vision for our data ecosystem. Working closely with executive and cross-functional stakeholders, you will drive innovation, deliver measurable business value, and build the foundation for future AI capabilities.

We are looking for a strategic leader with a proven track record of scaling high-performing Data & AI organizations, combining deep technical expertise with strong business acumen and the ability to lead large engineering teams in complex, high-scale environments.

Key Responsibilities:

Strategy & Organizational Leadership

• Own the overall Data & AI domain, including strategy, execution, delivery, and organizational growth.
• Define and drive the long-term vision, roadmap, and investment priorities for the company's data and AI platforms.
• Build, lead, and scale high-performing Data Engineering teams, engineering managers, and senior individual contributors.
• Establish a strong leadership culture focused on accountability, innovation, growth, and operational excellence.
• Drive organizational alignment and execution across multiple teams and stakeholders.
• Recruit, mentor, develop, and retain engineering leaders and top technical talent.

Platform Ownership & Technology Leadership

• Lead architecture and technology decisions for large-scale data ecosystems.
• Oversee the design, scalability, reliability, and governance of enterprise data platforms.
• Ensure excellence across Data Warehouses, Data Lakes, streaming platforms, analytics infrastructure, and AI-enabling systems.
• Drive adoption of modern engineering practices, observability, governance, security, and compliance standards.
• Establish frameworks for DataOps, platform reliability, and operational excellence.
• Build the technological foundations required to support future AI and machine learning initiatives.

Business Impact & Delivery

• Own business-critical data initiatives and ensure measurable impact on company KPIs.
• Partner closely with Product, Engineering, Analytics, Business, and Executive leadership teams.
• Translate business objectives into scalable data strategies and execution plans.
• Drive prioritization, resource allocation, roadmap planning, and delivery commitments across the domain.
• Lead large-scale cross-functional initiatives from concept through execution Identify opportunities where Data & AI can accelerate growth, improve efficiency, and drive innovation across the business.

Required Qualifications:

• 15+ years of experience within Data Engineering, Big Data, Data Platform, or related domains.
• 10+ years of leadership experience managing engineering teams.
• 5+ years of experience managing managers and senior engineering leaders.
• Proven success building and scaling Data Engineering or Data & AI organizations in complex, high-growth environments.
• Deep hands-on and architectural expertise across: Data Warehouses, Data Lakes and Lakehouse architectures, Batch and real-time processing systems, Data pipelines and orchestration frameworks, Data governance and quality programs, DataOps and MLOps methodologies, Data compliance and regulatory frameworks.
• Experience owning business-critical platforms with measurable performance and KPI outcomes.
• Strong understanding of cloud-native data architectures and distributed systems.
• Demonstrated ability to drive organizational scale, operational excellence, and delivery processes.
• Proven track record leading large cross-functional programs and initiatives.
• Strong business acumen with the ability to connect technical strategy to business results.
• Exceptional leadership, communication, stakeholder management, and influencing skills.
• High level of ownership with a strong focus on execution and outcomes.

Preferred Qualifications:

• Experience building AI/ML infrastructure or enabling AI-powered products and capabilities.
• Background in high-scale SaaS, technology, or data-intensive product companies.
• Experience leading organizational transformation, data modernization, or platform migration initiatives.
• Hands-on familiarity with technologies such as: Spark, Kafka, Flink, Airflow, Databricks, Snowflake, dbt, Similar modern data ecosystem technologies.
• Experience managing globally distributed engineering teams.
• Knowledge of modern AI platform architectures and machine learning operations.