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Required DevOps and Data Engineer
Job Location:
Israel, Hod HaSharon (Hybrid)
Job Brief:
Design, develop, and maintain internal data services, automation flows, CI/CD infrastructure, and database-related tooling.
Job Description:
Design, develop and maintain data pipelines, ETL/ELT flows, and integrations between internal engineering systems
Design and own the DevOps framework for the company and enable the automation infrastructure used by engineering teams
Build automation tools to improve data processing, tooling, and development workflows
Develop and help optimizing the in-house database-related services, including SQL queries, indexing, stored procedures, performance tuning, and monitoring
Ensure data security, permissions, access control, and data integrity across internal systems
Collaborate with cross-functional teams to understand requirements, solve technical issues, and improve internal developer and customer-facing platforms.

Required Staff Data Scientist
Job Description
As a Staff Data Scientist, youll play a highly embedded and influential role within our Data Science organisation, partnering closely with Development and Product teams across multiple products within ITOM. Rather than simply responding to predefined requirements, youll bring your own creativity, domain expertise, and ideas to identify opportunities, challenge assumptions, and solve complex problems using real customer data.
What you get to do in this role:
Lead the development and evolution of advanced data science and machine learning capabilities, including noise reduction, anomaly detection, root cause analysis, and new AI-powered product features.
Own complex data science problems end-to-end, from problem definition and ideation through experimentation, model development, evaluation, productionization, and deployment.
Develop advanced algorithms and models using techniques such as machine learning, deep learning, NLP, anomaly detection, and statistical modeling.
Partner closely with Product, Engineering, Quality, and Architects to translate product requirements into scalable, reliable ML solutions.
Drive technical direction and mentor other data scientists, contributing to best practices in modeling, experimentation, evaluation, and ML engineering.
Stay current with advances in AI/ML and identify opportunities to apply emerging technologies to our products.

we are looking for a AI Data Lead.
As Data Lead, you will own how data gets turned into decisions across the company - and lead the shift from traditional BI into AI-driven BI, powered by agents that surface insight in real time. You'll work closely with one data engineer today, with room to grow the team as scope expands.
You'll define what the data function looks like when AI is embedded in it, not bolted on - from the underlying infrastructure to the dashboards and agents people actually use. The playbook for AI-native BI is still being written, and you'll write a lot of it.
Key Responsibilities
Data Strategy & Ownership:
Own the vision and roadmap for the data function, including the shift from classic BI to agent-based, AI-driven BI
Set priorities in partnership with senior leadership
Work closely with a data engineer today, with the option to grow the team as the function scales
AI-Driven BI & Agents:
Drive adoption of AI across data workflows - from automating analyses to agents answering business questions in real time
Own the semantic and metrics layer so every dashboard and every agent reads the same definitions
Build in a git-based workflow: dashboards and queries live in git, edited through PRs, built with agents
Expose our data to agents over MCP so business questions get answered without waiting for a dashboard
Define where AI speeds things up - and where human judgment still has to hold the line
Infrastructure & Analytics:
Own the data infrastructure: BigQuery, dbt, pipelines, and data reliability
Lead complex analytics work, A/B testing, and impact measurement, hands-on
Define evals and quality metrics for AI features and agents - not just A/B tests on dashboards
Cross-functional Collaboration
Partner with product, marketing, finance, operations, and engineering to define analytical needs and turn them into solutions
Represent the data function to the organization - senior-level storytelling with data

Required Data Engineering Manager
Data, Ramat Gan, Israel (Hybrid)
Description
We are one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make peoples lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions.
As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.
If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!
Responsibilities:
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

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.

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.

Were looking for a Senior Data Engineer in the Data Collection Ingest team to contribute to the design and coding of our data ingestion services & pipelines. This role involves working as part of a team that handles millions of requests per minute across multiple servers, and is responsible for a wide-range of data pipelines, processing billions of events each day.
Why is this role so important?
As the most trusted platform for measuring online behavior, millions of people rely on our insights daily as the ground truth for their knowledge of the digital world. Producing these insights requires large scale raw data to be ingested reliably in high scale to provide stable signals for analysis. As a Data Engineer you will have the opportunity to perform hands-on work and own our raw data ingestion pipeline end-to-end. Your work will have a direct impact on the quality and reliability of our data and the insights that our products are delivering to our customers.
So, what will you be doing all day?
Your role as Data Engineer of the Ingest Data Collection team means your daily responsibilities may include:
Design, code and manage end-to-end our data ingestion pipelines, both online and offline.
Take charge of developing & maintaining modern data infrastructure, while implementing best practices for building data pipelines.
Be responsible for high-scale ingestion services, solving challenges of availability, reliability, and scalability.
Run the production environment by monitoring availability and taking a holistic view of system health and data quality.
Own data infrastructure features from design to production using industry best practices with focus on quality and delivery.
Lead design & decision-making processes of the team.
Solve diverse complex problems of scale, performance and business logic.
Collaborate with product managers and other team leaders to plan, nurture, and implement an efficient and effective development process.
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products
Perform code reviews, evaluate implementations, and provide feedback about potential improvements.
Improve your skills, learn from and mentor top-notch engineers and enrich other team members.
Have lots of fun!

Required Senior Data Engineer
Description
We are making the future of Mobility come to life starting today.
We support the worlds largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.
At the heart of our platform lies the data infrastructure, driving advanced machine learning models and optimization algorithms. As the owner of data pipelines, you'll tackle diverse challenges spanning optimization, prediction, modeling, inference, transportation, and mapping.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platform-supporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do:
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.

we are looking for a hands-on Data Platform Engineer to operate and evolve our enterprise Kafka ecosystem, which serves as the companys central data streaming platform. The role is critical to our data infrastructure and supports a major ongoing migration to the cloud, while covering production operations, troubleshooting, automation, maintenance, and reliability across high-volume, low-latency, 24/7 on-premises and cloud environments.
Responsibilities:
Operate and monitor Kafka environments across Confluent Cloud, Confluent Platform, and Kubernetes/CFK deployments, including availability, consumer lag, replication, throughput, latency, storage, and capacity.
Troubleshoot production incidents, participate in on-call, perform root-cause analysis, and improve resilience, failover, and disaster-recovery readiness.
Manage topics, partitions, retention, ACLs, consumer groups, Kafka Connect connectors, and Schema Registry.
Deploy, configure, upgrade, patch, and scale platform components and connectors while maintaining secure access and configuration consistency.
Automate platform operations and provisioning using scripting, infrastructure-as-code, and CI/CD.
Work with DevOps, SRE, Infrastructure, Security, Architecture, Data, and application teams to onboard workloads and continuously improve platform reliability and governance.