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Salary
≈ $82k – $206k per year (Estimated)
Location
Hybrid (Tel Aviv, Israel)
Seniority
Staff · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 5, 2026.

Overview
Company
Impact
Profile match
Unify omnichannel data, embed expertise, and orchestrate execution with Skai. Drive growth today. Build for what's next.

Description

Who are we?

Skai (formerly Kenshoo) is a leading omnichannel marketing platform that leverages advanced AI and data-driven performance media to enable smarter decision-making, increased efficiency, and maximized ROI for businesses worldwide. Our platform helps manage approximately $10B in annual ad spend through partnerships with Google, Meta, Amazon, Microsoft, and others.

Founded in 2006, Skai is a global company operating in a hybrid work model that combines remote flexibility with in-office collaboration. We continuously modernize our stack to handle commerce decisions at a massive global scale.

What will you do?

As the Infrastructure Engineering Lead, you will own the technical direction, architecture, and delivery of Skai’s core production data infrastructure (MySQL, SingleStore, Snowflake, Airflow, and Microservices).

In this role, you will balance in-house, open-source, and SaaS solutions to manage petabyte-scale data while ensuring system reliability, scalability, and cost-efficiency. You will blend hands-on engineering, technical architecture, vendor management, and team mentorship. You will lead cross-functional delivery, drive operational excellence across a 24/7 production environment, and set engineering guardrails for cloud-based data systems across the company.

Responsibilities:

  • Technical Leadership & Architecture: Set engineering guardrails, lead architectural reviews, lead the pod’s daily, and balance design tradeoffs for cloud-based data systems across all business units.
  • Execution & Delivery: Own the pod’s Scrum processes (epics, stories, tracking), balance technical debt management with rapid feature delivery, and drive multi-project execution.
  • Hands-on Engineering & Escalations: Stay active in code and infrastructure, serving as the primary technical escalation point for complex, 24/7 production issues.
  • Ops, High Availability & Reliability: Oversee operational readiness, rotation schedules, high availability (HA), backup and recovery processes, and automation to maintain 24/7 production uptime.
  • Mentorship & Team Culture: Raise the technical bar, foster a culture of engineering excellence, mentor team members, and drive professional growth within the pod.
  • Stakeholder & Vendor Alignment: Act as a strategic partner to align roadmap planning, bridge technical execution with business goals, and serve as the main point of contact for data infrastructure vendors.

Requirements

  • 5+ years of proven experience in a DBA, DevOps, DataOps, or Data Engineering role with deep hands-on ownership of production databases (e.g., MySQL, SingleStore, PostgreSQL).
  • Proven track record in designing, operating, and maintaining large-scale data infrastructure (capacity planning, performance tuning and upgrades, monitoring, CI/CD (Jenkins/GHA/ArgoCD)).
  • Strong software engineering capabilities in Python, Java, or Go within a microservices architecture, as well as Bash scripting.
  • Hands-on expertise with Linux environments and at least one major cloud provider (AWS preferred).
  • Demonstrated experience in leading technical design reviews, setting engineering guardrails, and mentoring engineers.
  • Strong analytical problem-solving skills with a data-informed approach to resolving complex, cross-system production issues in a 24/7 environment.
  • Exceptional communication, teamwork, and stakeholder management skills.

Advantages:

  • Experience with modern Big Data technologies at scale (e.g., Snowflake, Kafka, Spark).
  • Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform, Pulumi, or Ansible.
  • Previous experience as a Tech Lead, Team Lead, or Acting Lead on a mission-critical production team.
  • Working with AI tools / integrating AI into engineering and operational workflows.
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