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This is a full-time, on-site role for a Data Engineer Ltd., located in Haifa. The Data Engineer will design, build, and maintain scalable data pipelines, implement robust Extract, Transform, Load (ETL) processes, and develop efficient data models to support business intelligence and data analytics needs. The role also involves building and improving data warehousing solutions and collaborating with cross-functional teams to ensure data integrity and optimize workflows.

We are looking for a talented Data Operations student to join our Data team!
In this role, you will play a vital role in monitoring system performance and ensuring smooth operations. You will be responsible for flagging and solving incidents, prioritizing issues, and collaborating with R&D, Delivery, and Customer Partner teams
The role includes, 2-3 shifts a week, including nights shifts & weekends.
Responsibilities:
Monitor system performance and operations to ensure they meet performance and availability standards.
Flag and solve urgent incidents, escalating complex issues to appropriate teams when necessary.
Prioritize incidents based on urgency and impact, ensuring timely resolution.
Collaborate with R&D, Delivery, and Customer Partner teams to address operational issues and improve processes.
Implement monitoring-related processes, such as on-Call playbooks and reports, to ensure consistency of service level and ensure SLAs are met.
Prepare and provide regular status updates and reports on system performance and incident management.

We are looking for a Forward Deployed Egngineer with a strong performance marketing background to lead the deployment and success of our solution for a small number of enterprise customers.
You will own the full post-sale lifecycle, from implementation through ongoing optimization, working directly with growth, data, and engineering teams at some of the world's leading consumer apps. Your focus is on signal quality, experiment design, and driving measurable impact on paid acquisition performance.
This is a high-ownership role for someone who thinks in terms of ROAS, CPA, and bidding strategy, and can also get deep into data and systems to make it happen. You will be the primary point of contact for your accounts, lead engagements end-to-end, and translate performance data into clear decisions.
Success means turning your customers' best predictive signals into compounding growth on Google and Meta.
Responsibilities:
Performance and experimentation:
Design and structure pilots across Google Ads and Meta, including campaign selection, budget approach, bidding strategy, and success criteria
Evaluate experiment results and iterate based on performance signals
Help customers understand performance drivers, attribution, and how to scale what works
Monitor model and signal performance; identify issues early and intervene
Implementation and signal quality:
Lead end-to-end implementation across a small portfolio of enterprise customers
Adapt solution design and data strategy to each customer's ad tech stack and measurement setup
Ensure strong match rates, data accuracy, and signal reliability across conversion APIs and MMPs
Troubleshoot integration and data issues in collaboration with internal teams
Customer partnership and execution:
Own day-to-day execution across multiple engagements
Lead ongoing customer communication with both technical and senior growth stakeholders
Coordinate across product, engineering, and go-to-market teams
Build long-term trust through reliability and strong outcomes.

About GeoEdge GeoEdge is the global leader in ad security, trusted by hundreds of the world's top ad platforms, publishers, and app developers. Our mission: make the internet safer by stopping malicious, deceptive, and low-quality ads before they ever reach a user. For over a decade, we've protected the integrity of the digital advertising ecosystem with real-time technology that empowers our partners to deliver clean, trustworthy user experiences. The Role Malvertising attackers are already using AI to hide their campaigns. We're building the detection technology that beats them, and we need a leader who can make it the best in the world. As our Head of Security & Research, you'll report directly to the CEO and own GeoEdge's malvertising detection vision, combining deep security research with AI and agentic innovation. You'll lead our security research team, uncover new attack techniques before they reach users, and turn that insight into detection that works in real time at massive scale. You'll build a research agenda that puts GeoEdge on the stage at the world's top security conferences, and partner with Product, R&D, Data Science, Customer Support, and other key functions inside and outside the company to bring it to market. You'll be the security and research voice of GeoEdge for customers, partners, and the wider security community. What You'll Do Set the strategy and roadmap for GeoEdge's malvertising detection and security research Lead, mentor, and grow the security research team Drive AI and agentic innovation in detection, working with R&D and Data Science to turn research into production-grade capabilities Uncover and track emerging malvertising threats, evasion techniques, and attacker campaigns across the ad ecosystem Own detection quality: push for uncompromising precision, coverage, and speed Drive original research and publications, and represent GeoEdge at leading security conferences Partner with Product, R&D, Data Science, Customer Support, and other key functions in the organization and outside of it Report to the CEO and management on research impact, threat landscape, and priorities

We are looking for the next Data Analyst to join our growing team!
If you enjoy working in a dynamic and fast-paced startup environment, this opportunity is perfect for you! Our customers come from a wide range of industries, populating our datasets with extraordinary amounts of rich and diverse data.
Responsibilities:
You will be a part of the Data team and work with a wide range of data sources and types
Be an integral part and improve our data pipeline and the client onboarding process
Be in charge of analyzing complex datasets and translating them into valuable insights.
Work closely with our clients and understand their needs.
Data visualization both for internal and external purposes.
You will take a significant role in the AI model design and creation
Build data analysis infrastructure.

We are looking for a Lead Software Engineer - Innovation Team to join our growing our new engineering innovation team who build our new product offering with our clients!
Our newest product line - a small, fast-moving team operating like a startup inside the company. While our core offering helps customers acquire better users and spend less doing it, Engage turns that intelligence inward: re-activating churned, dormant, and low-value users who are already on our customers' platforms. As a Senior Software Engineer, you'll work directly alongside the team's engineering lead, building the systems that take machine-learning predictions about user behavior and turn them into automated, continuously-learning decisions delivered straight into our customers' DB and CRM tools. This is a role with no narrow lane - you'll touch literally everything: data pipelines, ML and algorithms, applicative backend services, and even the UI. You'll partner closely with a VP Product and senior data scientists in a high-ownership environment where you shape the architecture, ship to production, and see your work drive a brand-new revenue stream for the company.
Responsibilities:
Design and build high-quality, production-grade systems across the entire Engage stack, from large-scale cloud data pipelines, to ML and decisioning services, to applicative backend and customer-facing UI, with an eye for performance, reliability, and easy maintenance.
Own the closed loop end-to-end: turning ML predictions into automated decisions, delivering them into customers' DB and CRM systems, and feeding outcomes back in so the system keeps learning.
Take features from idea to production largely on your own: designing the architecture, shipping it, monitoring it in production, and iterating, with the autonomy (and accountability) that comes with a small team.
Collaborate closely with the team's engineering lead, the VP Product, and senior data scientists to take models and research from prototype to reliable, scaled-up production systems.
Monitor performance and prioritize work by making data-driven decisions.
Participate in code reviews and uphold engineering standards and best practices across the team.

Were looking for a talented AI-native Software Engineer to join our innovative R&D team!
We help our customers acquire better users and spend less doing it - and our core team owns the engine behind it. We turn raw customer data into ad-network conversions, end-to-end: through large-scale ML and data pipelines, event-driven delivery services on AWS, and the UI that ties it together. There's no narrow lane here - you own problems wherever they live in the stack.
We're an AI-native team: we treat AI and agentic tooling as a first-class part of how we build, and it's how a small team credibly owns this much surface area. We're looking for a high-ownership generalist who works this way (or is hungry to), and who thrives in a correctness-critical domain where a bug means real customer ad-spend going the wrong way.
Responsibilities:
Turn raw customer data into ad-network conversions end to end, building across the whole stack: ML and data pipelines, delivery services, and the customer-facing UI.
Take features from idea to production largely on your own, designing, shipping, monitoring, and iterating, using AI and agentic tooling as a force multiplier, and owning your systems in production where mistakes translate directly into customer spend.
Collaborate closely with the team lead, product, and data scientists to take models and ideas from prototype to reliable, scaled-up production.

We are looking for a Senior Data Scientist to lead the design and implementation of next-generation AI solutions for Lifecycle Marketing.
As a senior member of our team, you will shape methodology, guide product direction under uncertainty, and represent us in high-stakes conversations with customers. Youll combine deep expertise in causal inference, reinforcement learning, and experimentation with strong communication skills to drive impact across the company and with our clients.
Responsibilities
Own the design and methodology of data science solutions for lifecycle marketing, with emphasis on causal inference, uplift modeling, and reinforcement learning.
Lead the development of experimentation frameworks (A/B/n tests, variance reduction, policy evaluation).
Research, prototype, and productionize multi-armed bandits and contextual RL approaches for personalization and timing optimization.
Take a strong, opinionated role in brainstorming sessions, guiding decision-making in areas of high uncertainty.
Represent us in front of customers, translating complex modeling decisions into clear business value.
Mentor junior and mid-level team members, raising the technical bar across the team.
Collaborate closely with product managers, engineers, and analysts to align data science strategy with business goals.

We are looking for a Senior Software Engineer to join our growing Data Infrastructure team!
The team's main responsibility is developing our data platform - from building the microservices and pipelines that onboard customer data into our platform, to the infrastructure and tooling that enables our internal data teams to analyze, transform, process, and collect data independently. Our goal is to build leverage: every feature we ship reduces friction for the teams that depend on our platform. We're looking for a builder who takes full ownership from inception to production, cares deeply about quality and performance, and leverages AI tools to move faster and deliver better outcomes.
Responsibilities
Design and implement scalable, production-grade data pipelines and microservices that ingest, transform, and move data from a wide variety of customer sources at high volume.
Build and maintain high-performance backend services and APIs that interface with our data ecosystem, ensuring reliability, low latency, and security.
Develop and evolve the platform infrastructure - data warehouse, orchestration, compute - that internal data teams rely on daily.
Identify opportunities to automate recurring workflows and turn ad-hoc needs into robust, self-serve platform capabilities.
Collaborate with data scientists, analysts, and engineers across R&D to translate requirements into platform features.
Drive code quality through design reviews, code reviews, and adherence to engineering best practices.
Leverage AI tools throughout the full engineering cycle - from scoping and design to implementation and debugging - to deliver faster, higher-quality outcomes.

We are seeking a hands-on, business-oriented DevOps Team Lead to spearhead our infrastructure and cloud operations. You will build and maintain the foundational systems enabling our agentic AI ecosystem while leading a team of talented engineers to translate technical capabilities into commercial impact.
Our core technology uses advanced AI predictive models (LTV, churn, and intent). You will ensure the high-performance infrastructure required for autonomous signal engineering and real-time recalibration of these models is optimized for performance and ROI.
In this role, you will bridge the gap between infrastructure excellence and business strategy, ensuring our technical roadmap is optimized for both performance and ROI.
Responsibilities:
Leadership & Hands-on Execution: Manage and mentor a high-performing DevOps team while remaining deeply involved in technical execution, architecture, and troubleshooting.
AI-Driven SDLC: Continue evolving our software development lifecycle by integrating AI-driven methodologies and agentic AI tools to automate delivery, improve code quality, and accelerate release cycles.
Infrastructure Management: Own and optimize our core cloud infrastructure on AWS and our data warehouse environment on Snowflake.
Resource Management & ROI: Take accountability for the cloud infrastructure budget. Monitor costs, manage vendor relationships (SaaS & AI tooling), and ensure all resource allocations drive tangible business value.
Security & Compliance: Enforce rigorous security standards and data privacy protocols across all infrastructure and engineering workflows to protect our product ecosystem.