עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
מלאה
30,000-45,000 ₪
We are seeking a Data Infrastructure Team Lead to join our Platform group. In this role, you will build and lead the team responsible for data infrastructure foundation - the systems that power our product experiences, trusted analytics, AI capabilities, and enterprise-scale operations.
Data infrastructure is not just about moving data from one place to another. It is about building reliable, scalable, and secure infrastructure that helps product and engineering teams move faster, enables smarter customer-facing experiences, supports trusted business decisions, and creates the foundation for safe AI adoption across the company.
This is a leadership role for someone who stays close to the technology: setting direction, guiding architecture, reviewing designs, contributing to critical decisions, and working with the team through complex production and scaling challenges.
You will design and evolve scalable, reliable, secure, and AI-ready data systems, including orchestration, streaming, distributed storage, analytical infrastructure, metadata and governance capabilities, and permission-aware data access for sensitive HR data.
Data infrastructure is not just about moving data from one place to another. It is about building reliable, scalable, and secure infrastructure that helps product and engineering teams move faster, enables smarter customer-facing experiences, supports trusted business decisions, and creates the foundation for safe AI adoption across the company.
This is a leadership role for someone who stays close to the technology: setting direction, guiding architecture, reviewing designs, contributing to critical decisions, and working with the team through complex production and scaling challenges.
You will design and evolve scalable, reliable, secure, and AI-ready data systems, including orchestration, streaming, distributed storage, analytical infrastructure, metadata and governance capabilities, and permission-aware data access for sensitive HR data.
Requirements:
Proven experience designing, building, and operating large-scale data infrastructure in production environments.
Strong engineering fundamentals in databases, distributed systems, concurrency, storage, and reliability.
Strong knowledge of analytical engines, columnar databases, and data warehouse/lakehouse architectures.
Experience with data orchestration tools and distributed storage solutions.
Understanding of data security, privacy, governance, lineage, auditability, and access control.
Ability to make pragmatic architecture decisions, balance maitenance-vs-delivery tradeoffs, and optimize for scalability, reliability, simplicity, and cost.
Proven ability to lead a team, mentor engineers, communicate clearly, and work effectively with cross-functional stakeholders.
Experience building infrastructure for data pipelines, orchestration, streaming, analytical workloads, and large-scale data processing.
Experience with observability, monitoring, alerting, incident management, SLOs, and production operations for data systems.
Strong understanding of AI-ready data platforms, including metadata, semantic layers, retrieval patterns, data quality, governance, and permission-aware access to data.
Expertise with relational databases; PostgreSQL experience is a plus.
Hands-on experience with streaming systems such as Apache Kafka or equivalent technologies.
Bonus Skills
Experience with cloud-based data infrastructure solutions, such as AWS or GCP.
Familiarity with Kubernetes.
Experience with modern lakehouse technologies, open table formats, metadata catalogs, or data governance platforms.
Experience supporting AI, ML, LLM, semantic search, or agentic product use cases on top of production data.
Experience building multi-tenant SaaS infrastructure, especially with sensitive or permission-heavy data.
Experience with cost optimization and FinOps practices for data platforms.
Experience creating internal developer platforms, self-service data tooling, or paved-road infrastructure for engineering teams.
Proven experience designing, building, and operating large-scale data infrastructure in production environments.
Strong engineering fundamentals in databases, distributed systems, concurrency, storage, and reliability.
Strong knowledge of analytical engines, columnar databases, and data warehouse/lakehouse architectures.
Experience with data orchestration tools and distributed storage solutions.
Understanding of data security, privacy, governance, lineage, auditability, and access control.
Ability to make pragmatic architecture decisions, balance maitenance-vs-delivery tradeoffs, and optimize for scalability, reliability, simplicity, and cost.
Proven ability to lead a team, mentor engineers, communicate clearly, and work effectively with cross-functional stakeholders.
Experience building infrastructure for data pipelines, orchestration, streaming, analytical workloads, and large-scale data processing.
Experience with observability, monitoring, alerting, incident management, SLOs, and production operations for data systems.
Strong understanding of AI-ready data platforms, including metadata, semantic layers, retrieval patterns, data quality, governance, and permission-aware access to data.
Expertise with relational databases; PostgreSQL experience is a plus.
Hands-on experience with streaming systems such as Apache Kafka or equivalent technologies.
Bonus Skills
Experience with cloud-based data infrastructure solutions, such as AWS or GCP.
Familiarity with Kubernetes.
Experience with modern lakehouse technologies, open table formats, metadata catalogs, or data governance platforms.
Experience supporting AI, ML, LLM, semantic search, or agentic product use cases on top of production data.
Experience building multi-tenant SaaS infrastructure, especially with sensitive or permission-heavy data.
Experience with cost optimization and FinOps practices for data platforms.
Experience creating internal developer platforms, self-service data tooling, or paved-road infrastructure for engineering teams.
This position is open to all candidates.
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
תל אביב - יפו
