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We are looking for a Data Architect / Hands-On Lead to join our Data Analytics team and lead the design and delivery of complex data solutions in a highly technical environment.
What will you do?
Design and lead Data architectures end-to-end
Work hands-on with GCP and cloud-based data solutions
Design, develop, and implement scalable Data solutions
Provide technical leadership across complex projects and Data analytics teams
Drive architectural decisions and technology selection based on business and technical needs
Collaborate with Data Engineering, Cloud, BI, Database, and other technical teams
Mentor and guide engineers and technical professionals
Stay hands-on and involved in solving complex technical challenges
Work across multiple customers, projects, technologies, and architectures.

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 a Senior Data Engineer with strong Python expertise and extensive experience building large-scale, distributed data systems.

You will play a key role in developing our next-generation data platform, building integrations with external data sources, and designing the services and pipelines that collect, process, and serve large volumes of data across our product.

You will own systems throughout their full lifecycle - from system design and hands-on development to deployment, scalability, and production monitoring - while contributing to technical decisions and working closely with the team on building reliable, high-performance data solutions.

Our Office is located in Kiryat Ono.This is a hybrid position, including two work-from-home days per week, with flexibility .

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.

Required Senior Data Engineer
About the role:
You will specialize in designing and building world class, scalable data architectures, ensuring reliable data flow and integration for groundbreaking biotechnological research. Your expertise in big data tools and pipelines will accelerate our ability to derive actionable insights from complex datasets, driving innovations in improving patients outcome and in delivering life savings treatment solutions.
In this role, you will work closely with data scientists, AI/ML engineers, architect and other cross-functional teams to understand their data needs and requirements. You will also be responsible for ensuring that data is easily accessible and can be used to support data-driven decision making.
Location: Ramat Gan, (Hybrid model)
What will you do?
Design, build, and maintain data pipelines that ingest, transform, and load noisy, heterogeneous biological data at scale - from single-cell sequencing, genomic, and clinical sources - across databases, APIs, and flat files
Enhance our data warehouse system to dynamically support multiple analytics use cases
Implement and productize complex scientific and computational algorithms as scalable, production-grade pipeline components
Drive our data infrastructure toward becoming AI-native, enabling AI/ML systems and agents to reliably query, reason over, and act on our data
Implement data governance policies and procedures to ensure data quality, security, and privacy
Collaborate with ML and AI scientists and other cross-functional teams to understand their data needs and requirements
Drive team capability growth by championing an AI-first SDLC, mentoring data engineers on AI-assisted development practices and tooling
Develop and maintain documentation for data pipelines, processes, and systems
Requirements
We will only consider senior data engineers that have demonstrated strong system design skills combined with an extensive background working with data orchestration, data warehousing and ETL tools.

We are looking for an experienced Data Infrastructure Team Lead to lead our Data Infrastructure team. In this role, you will have formal people-management responsibility for a multidisciplinary team that builds, productionizes, and improves big data and analytics infrastructure. You will be responsible for team delivery, combining technical depth, agile leadership, and an AI-first mindset to help the team build reliable systems, improve how it works, and continuously raise its engineering standards.
Location: Ramat Gan (Bursa area), Israel - Hybrid model
What will you do?
Lead, manage, and develop a data infrastructure team of approximately 5-7 people.
Take responsibility for team delivery, including planning, prioritization, execution, and continuous improvement.
Lead agile ways of working, including scrum-based delivery practices.
Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure.
Partner closely with cross-functional stakeholders across technical, scientific, and business interfaces.
Help the team adopt AI-first engineering practices, including automation and AI-assisted development workflows.
Drive improvements in team processes, technical quality, delivery predictability, and collaboration.
Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems.
Create an environment where team members can grow, contribute, and improve together.

Required Customer-Facing Data Scientist - Demand Forecasting
Demand Forecasting Team:
The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities:
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of our Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

Were looking for an Infrastructure Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Infrastructure Team Manager in the R&D.
Why is this role so important?
A data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As a Data Infrastructure Engineer in the Datalabs group, you will be the technical backbone supporting our data production, analyst, and data science teams. You will own and maintain our AWS cloud accounts and Databricks workspaces, optimize pipeline executions, and proactively modernize our tech stack to reduce tech debt - ensuring our platform remains scalable, reliable, fast, and cost-effective.
Given the business-oriented nature of Datalabs, you will work closely with cross-functional stakeholders and internal teams who interface directly with strategic customers. By unblocking operational bottlenecks and building robust tooling, you will empower our analysts and data scientists to deliver custom, high-value data products to our customers seamlessly.
So, what will you be doing all day?
Environment & Workspace Management: Administering and optimizing our groups AWS cloud accounts, IAM policies, and Databricks workspaces to ensure peak performance, rock-solid security, and cost efficiency.
Execution & Pipeline Infrastructure: Owning the health, reliability, and scaling of our core data execution environments (Airflow, Docker, EKS/ECS, distributed queues, and database engines).
Tech Debt Modernization: Proactively researching, benchmarking, and replacing legacy debt with modern technologies to keep our platform fast and cutting-edge.
Developer & Production Support: Serving as the technical focal point for internal analysts and data science teams-providing the tooling, standards, and infra support they need to build custom client reports smoothly.
Cross-Group & Client Alignment: Partnering with external engineering teams and internal stakeholders to support custom data delivery pipelines and uphold high-priority customer SLAs.