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Required Data Engineering Lead
Why this role matters:
Data isn't just for dashboards - it's the nervous system of our future products. As we expand into smart lighting (Oasis) and living tech (Easyplant), we need to process massive streams of IoT signals and power real-time AI. You won't just maintain a warehouse; you will architect the platform that connects our physical products to the digital world.
What youll do:
Build the "Brain": Architect the next-gen data platform capable of handling high-volume IoT streams and integrating AI capabilities into our daily operations.
Code the Core: This is a hands-on role. You wont just manage; youll be deep in Python, DBT, and Airflow, building and optimizing the pipelines yourself.
Scale for Complexity: We are growing from one product to a multi-brand ecosystem. You will ensure our data infrastructure evolves to support diverse business lines without becoming a bottleneck.
Democratize Insights: Build a system so robust and intuitive that every engineer, product manager, and marketer can self-serve the data they need to build better products.

We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
What you'll do:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

We're looking for a Senior Data Scientist who loves what they do: a strong foundation in machine learning, statistics, and software engineering, a passion for modern AI-accelerated development, and the drive to own research, design, and end-to-end delivery of ML systems that ship to millions.

What you'll be doing


Research, train, and deploy state-of-the-art recommender systems using deep learning and GenAI
Own projects end-to-end - from business idea through modeling, experimentation, and production deployment - including the parts that involve aligning other people around them
Build online, scalable models and serving solutions that leverage massive datasets and reach hundreds of millions of users
Apply multimodal and sequence-modeling techniques to real product problems where model improvements translate directly to business impact
Lead cross-team initiatives, improve the tooling the team works with every day, and mentor others as you go
Collaborate with ML experts, big data engineers, product managers, and developers across the organization to solve complex problems

we are on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Software & Data Engineer at our company, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how our company understands and improves its service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our company's engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how our company operates
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.

As we scale and evolve our fully automated fraud prevention strategies, we are seeking a Data Analyst to join our growing Fraud Analytics team.

We operate in a data-rich, fast-paced environment, processing billions of data points annually, and play a critical role in safeguarding large enterprises from fraud. In this role, you will work at the intersection of data analysis, fraud strategy, and automation, collaborating closely with engineering, data science, and commercial teams to develop scalable fraud detection solutions.

This is a high-impact role with significant ownership and cross-functional collaboration in a team with tremendous room for growth. If you are highly motivated, data-driven, and thrive in a fast-moving environment - you belong with us.

Key Responsibilities

Develop and refine fraud detection strategies by analyzing complex datasets and identifying fraud patterns.

Partner with cross-functional teams, including software engineers, data scientists, and commercial stakeholders, to develop scalable fraud solutions.

Conduct deep-dive risk analyses, leveraging multiple data sources to assess fraud threats and define innovative solutions.

Monitor and automate fraud detection processes to enhance efficiency and effectiveness.

As we scale and evolve our fully automated fraud prevention strategies, we are seeking a Senior Data Analyst to join our growing Fraud Analytics team.

We operate in a data-rich, fast-paced environment, processing billions of data points annually, and play a critical role in safeguarding large enterprises from fraud. In this role, you will work at the intersection of data analysis, fraud strategy, and automation, collaborating closely with engineering, data science, and commercial teams to develop scalable fraud detection solutions.

This is a high-impact role with significant ownership and cross-functional collaboration in a team with tremendous room for growth. If you are highly motivated, data-driven, and thrive in a fast-moving environment - you belong with us.


Key Responsibilities

Develop and refine fraud detection strategies by analyzing complex datasets and identifying fraud patterns.

Partner with cross-functional teams, including software engineers, data scientists, and commercial stakeholders, to develop scalable fraud solutions.

Conduct deep-dive risk analyses, leveraging multiple data sources to assess fraud threats and define innovative solutions.

Monitor and automate fraud detection processes to enhance efficiency and effectiveness.

We are looking for a highly skilled Senior Data Platform Engineer to join our Data Platform team and play a key role in designing, building, and evolving the companys data infrastructure.

This is a hands-on engineering position focused on developing scalable data platforms, high-volume ingestion pipelines, and the foundational data systems that power analytics, product applications, AI workloads, and large-scale model execution. You will help architect our data lake, build reliable ingestion capabilities at scale, and shape the core infrastructure that supports the companys future growth.

This is an exciting opportunity to work with cutting-edge technologies and have a defining impact on the architecture and evolution of our data platform.


What Youll Do
Build complex, high-volume batch and near-real-time ingestion services while helping evolve the platforms streaming capabilities.
Design and implement data solutions for all application requirements in a distributed microservices environment
Develop and optimize large-scale data pipelines for batch and streaming use cases.
Ensure data quality, compliance, and governance.
Manage and optimize Kubernetes infrastructure, utilizing KEDA to dynamically scale resources for large-scale data processing workloads.
Own the full lifecycle of our data stack using Terraform and Kubernetes, from provisioning to application-level frameworks.
Provide technical guidance for the team, drive best practices around infrastructure, CI/CD, testing, and system design.
Deep-dive into memory management and performance tuning to ensure our large-scale distributed systems are both cost-effective and lightning-fast.

We are seeking a Senior Backend Engineer - Data Platform to join our expanding team and play a crucial role in designing, building, and maintaining robust and scalable data pipelines and infrastructure. In this role, you will directly enable data-driven decision-making and support the development and deployment of AI/ML products that power Health.
Youll collaborate closely with engineering, product, and data science teams to ensure our data systems are high-quality, resilient, and scalable as we grow. As a Senior Backend Engineer on our Data Platform team, you will drive efforts to deliver reliable, efficient, and consistent data services across the organization. You will also help enable the rapid development and deployment of advanced features, insights, and AI-driven capabilities that improve outcomes for clinicians and clients.

Required Data Platform Engineering Team Leader
As a Data Platform Engineering Team Leader on the Infrastructure R&D Department in our Tel Aviv office, youll lead the engineering team behind the data platform powering our reporting, billing, experimentation, ML training, and revenue optimization. Youll shape the technical direction of one of our most critical platforms, grow exceptional engineers, and solve complex data infrastructure challenges at massive scale-building systems that are reliable, scalable, and easy to use.
How youll make an impact:
Lead, mentor, and grow a team of talented software engineers while fostering technical excellence and ownership.
Define the teams technical strategy, roadmap, and architecture for one of our core data platforms.
Own the reliability, scalability, and performance of the data pipelines powering reporting, billing, experimentation, and ML training.
Partner with engineering, product, finance, and ML teams to align priorities and deliver high-impact platform capabilities.
Drive the adoption of modern data technologies and AI-powered engineering practices to improve developer productivity and platform evolution.
Stay hands-on by reviewing architecture, code, and technical designs, while helping the team solve complex engineering challenges.
Guide the evolution of the Spark SQL platform and shared data infrastructure used across R&D.
Represent the team in architecture reviews, hiring, incident postmortems, and technical forums.

Required Senior Data Scientist
Realize your potential by joining the leading performance-driven advertising company!
As a Senior Data Scientist on the Algorithms team in our Tel Aviv office, youll play a vital role in designing and deploying machine learning models that power real-time bidding and optimize billions of daily auctions. Youll develop advanced modeling solutions that drive bid optimization, price prediction, and auction strategy while partnering closely with Engineering, Product, and Business teams to bring research into production. Your work will directly improve advertiser performance, publisher revenue, and marketplace efficiency at massive scale.
How youll make an impact:
Design, train, and deploy machine learning models for bid optimization, price prediction, win-rate prediction, CTR/CVR estimation, calibration, and auction optimization.
Own the full machine learning lifecycle, from research and experimentation through production deployment, A/B testing, monitoring, and continuous optimization.
Analyze large-scale marketplace data to identify modeling opportunities and translate insights into measurable business impact.
Partner closely with Product, Engineering, and Business teams to define and deliver scalable machine learning solutions.
Improve the performance, scalability, and reliability of production models serving low-latency, high-throughput traffic.
Mentor junior data scientists and contribute to technical reviews, experimentation best practices, and knowledge sharing across the team.

We are building next-generation SaaS security intelligence and SaaS Security Posture Management (SSPM) solutions that protect enterprises worldwide. If you enjoy turning complex security data into actionable insights and delivering end-to-end systems, this role is for you.
About the role
You will own, build, and maintain our data pipeline (Python) and enrichment system on top of PostgreSQL and BigQuery. This system powers security analytics, detections, and intelligence. A core part of your job will be to design and implement new components, improve reliability and performance, and ensure data quality and observability.
Key Responsibilities
Own, build, and maintain production data pipelines and enrichment services using Python, PostgreSQL, and BigQuery in a GCP cloud environment.
Architect data systems end to end, including design, deployment, monitoring, and iterative improvement.
Analyze complex security datasets and SaaS telemetry to uncover risks, patterns, and opportunities.
Research emerging threat vectors and contribute to automated intelligence feeds and published reports.
Work across security domains such as SSPM, Shadow Integrations, DLP, and Malware Protection.

We are looking for an experienced Data Engineer to own and evolve data infrastructure and analytics platform.

You will design and build scalable data pipelines and data models, working with large and diverse datasets generated across Trigos global retail deployments. You will own the data lifecycle from ingestion and transformation through orchestration, reliability, and analytics-ready datasets.

As a key technical owner of data platform, you will also work closely with analysts, Product, R&D, Operations, and Customer Success to build trusted data products, evolve our BI semantic layer, and turn complex data into scalable solutions

A day in the life
Design, build, and maintain scalable ETL/ELT pipelines processing large and diverse datasets.
Own and evolve data architecture, from ingestion and transformation through analytics-ready data models and consumption.
Build reliable data workflows and orchestration processes, with a focus on scalability, performance, and maintainability.
Design and maintain curated data models that power analytics, operational workflows, and data-driven products.
Ensure data quality, observability, monitoring, and reliability across datasets and pipelines.
Develop and evolve the BI semantic layer, enabling trusted metrics and self-service analytics across the company.
Work closely with R&D and Product on data integrations and new data-driven capabilities, including use cases that bridge offline analytics and production systems.
Partner with analysts and business stakeholders to translate complex requirements into scalable data solutions.

Required Engineering Team Lead - Data Science Team
About the Role:
A top player in its game and is heading for an exciting year.
In this role, you will take an integral part in the creation of a new and innovative SaaS product.
If you are a talented software engineer and engineering manager that likes to solve complex problems and looking for your next challenge we want you to join our team!
What youll do:
As the Team Leader of a Detection and Response Engineering team, you will lead a talented team to design, implement, and deploy scalable data solutions for an innovative SaaS product. Youll be responsible for shaping the direction of a system that impacts millions of users worldwide. If you're an experienced manager with a strong technical background, ready to lead in a dynamic, fast-paced production environment, we want you on our team!
The group responsible for 4-5 different products:
1. DRS (fully managed fraud detection solution)
2. Agentic Visibility
3. Citadel (ITP) - lean version of DRS capabilities
4. Transaction Monitoring offering
5. More might come soon
Responsibilities:
Lead and guide one of the DRS Engineering teams in the design and deployment of scalable data infrastructure.
Collaborate effectively with cross-functional teams (Data Science, Research, Security, etc.) to ensure alignment on business needs and security standards.
Manage the technical backlog, make critical decisions on product milestones, and ensure timely, secure, high-quality delivery and deployment.
Foster the growth of team members through mentorship, personal development opportunities, and the promotion of continuous improvement.
Identify, manage, and mitigate security risks across the data platform, maintaining high standards in all initiatives.
Define and implement methodologies to guarantee the performance, scalability, and quality of our data infrastructure.

This role combines deep technical expertise with leadership responsibility, driving multidisciplinary Data Science initiatives end-to-end within complex security policy management systems.

The role drives the development of innovative, production-grade AI capabilities, including the intelligence behind security AI agents and advanced machine learning models built on complex security data.

Original thinking, deep technical rigor, intellectual agility, and exceptional problem-solving are essential.

Responsibilities:

Lead end-to-end Data Science initiatives from problem framing through validation, CI/CD-based production deployment, monitoring, and ongoing operational optimization of AI systems

Develop advanced ML capabilities, including predictive modeling, anomaly detection, classification, and behavioral analysis

Develop the intelligent capabilities behind security AI agents, combining machine learning, LLMs, statistical methods, and domain-specific algorithms, with a strong understanding of how agents use these capabilities within multi-step workflows

Adapt and fine-tune LLM technologies for domain-specific security use cases

Define and implement rigorous evaluation methodologies for ML and agentic AI systems, including decision quality, reliability, robustness, uncertainty, and failure modes

Partner with Product, Engineering, and Security teams to deliver measurable business impact

Provide technical leadership and mentorship across multidisciplinary Data Science initiatives

Were growing and looking to hire a Director of Data & AI who embodies our core values: People First, Customer Obsession, Strive for Excellence, and Integrity.
About the Company:
A global leader in cyber-physical systems (CPS) protection, dedicated to securing the critical infrastructure that keeps the world running. Were a fast-growing, award-winning team where innovation meets purpose-and we want you to help us define the future of cybersecurity.
Our technology strategy is focused on solving real-world cyber-physical security problems at scale through robust, distributed, cloud-native architectures. We design and evolve a unified platform that serves as the technological backbone for all our products, delivering deep visibility across CPS environments-without disrupting critical operations. Our architecture emphasizes scalability, resilience, and extensibility to support both cloud and on-prem deployments.
About the Role:
We are seeking a visionary Director of Visibility to lead our core technology engine. This is a highly unique role that demands both top-tier professional expertise in cybersecurity research and the ability to seamlessly integrate Data Science and AI in a precise, highly productive manner. We have ambitious visibility goals that require uncompromising accuracy. Your mission is to combine precise, in-depth professional understanding of Cyber-Physical Systems (CPS/XIoT) with the immense scale and capabilities of AI. You will lead a multidisciplinary group comprising Data Science, Network/Protocol Research, and Asset Classification teams to revolutionize how we discover, classify, and secure critical assets across industrial (OT) and healthcare (IoMT) environments.
Responsibilities
As a Director of Data & AI your impact will be:
Multidisciplinary Leadership: Manage, mentor, and synchronize three distinct teams (Data Science, Network Research, and Asset Classification), ensuring cross-functional synergy and unified product delivery.
Scaling Accuracy with AI: Architect our visibility solutions to achieve unparalleled precision. Blend deep professional domain knowledge with advanced ML to scale asset discovery without sacrificing the exactness required in critical infrastructure.
Feature Engineering & Parsing: Oversee the translation of obscure, undocumented industrial and medical protocols into actionable features for our AI models.
Cross-Department Collaboration: Work closely with various data groups, product management, and R&D teams to translate network visibility into actionable risk management, segmentation, and threat detection policies.
Advanced Data Fusion & Collection Strategy: Manage diverse collection techniques (passive, active, and integrations), and architect how to fuse information for every single device at the scale of AI-bridging applications, algorithms, LLMs, and beyond.