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we are looking for a 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 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.

we are looking for a Senior Data Scientist
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.

We're building the data foundation that will power at massive scale. We're looking for a battle-tested Data Engineering Tech Lead who has built and scaled data infrastructure at companies where the bar is exceptionally high.
This is a ground-up, architect-and-build role. You'll own the entire data infrastructure layer - caching, indexing, storage architecture, scalability patterns - and set the standard for how data flows across the organization at scale.
What Youll be Doing:
Own and architect \entire data infrastructure from the ground up - storage, caching, indexing, and platform foundations.
Make the hard technology calls: which databases, caching layers, orchestration systems, and data patterns we adopt - and why - based on scale, performance, and long-term engineering excellence.
Drive data scalability across the engineering organization, partnering closely with platform, backend, and product engineers.
Lead hands-on - you design, you build, you review, you mentor.

abra professional services is seeking a talented Data Engineer! We are looking for a Data Engineer to join our team and work on cutting-edge AI projects. In this role, you will be responsible for ingesting large volumes of new data, as well as deeply understanding and analyzing it in close collaboration with our Data Scientists. You will design and develop critical, diverse, and large-scale data pipelines across both Cloud and On-Premises environments.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make our data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for our data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

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 to own high-impact data products from architecture through production deployment, monitoring, and continuous improvement. This isnt a pure infrastructure role - youll combine strong engineering with product thinking, operational excellence, and awareness of data quality, cost, and business impact.

You will design, implement, test, deploy, and maintain production-grade data products - pipelines, transformation layers, data quality and reliability systems - using tools like DBT (on Spark) and Databricks. Youll apply best practices in Python and SQL to build scalable and maintainable data transformations, and leverage technologies like LLMs and GenAI to create innovative solutions for real business problems.

This role is ideal for someone who wants technical leadership responsibilities in an AI-first engineering culture - we use LLMs, GenAI, and AI-native development tools as core parts of our daily workflow.

Key Responsibilities

Act as a technical leader within the team - raise engineering standards, drive strong architectural choices, and improve how we build
Own data products end-to-end: design, development, deployment, monitoring, and iteration
Work closely with senior leadership to translate strategic goals into scalable data solutions
Develop and maintain production ETL/ELT pipelines using DBT (on Spark) and orchestrated workflows in Databricks
Build monitoring, alerting, and testing pipelines to ensure reliability and performance in production
Evaluate and introduce new technologies - including AI-native development tools - and integrate the ones that create real impact
Collaborate with customers and external data providers - gathering requirements and making product decisions.
Mentor team members through code reviews, pairing, and knowledge sharing

our company has every ingredient of a marketplace business - advertisers, publishers, OEMs, carriers, consumers, devices, and proprietary device-level data. Our job in Data Science is to turn that raw advantage into intelligence: the insights, models, and experiments that optimize the marketplace and prove the value we create.
As a Senior Data Scientist, you'll partner with engineering, product, and business leaders to drive analysis that shapes strategy - from bidding efficacy and audience curation to measurement, attribution, and our centralized experimentation platform. You'll help DT build a culture of continuous, evidence-based improvement across every product surface.
About the Senior Data Scientist Role
Frame ambiguous business problems as crisp, testable data and modeling questions, and deliver analysis that informs product and commercial strategy
Design and analyze experiments (A/B and beyond) and help establish DT's centralized experimentation tracking - a single source of truth for hypotheses, results, and decisions
Build statistical and ML models for audience segmentation, bid/UA optimization, lifetime value, and measurement/attribution
Develop time-series and real-time event understanding that improves the timeliness and relevance of recommendations and bidding
Partner with ML and Data Engineering to productionize models and feed insights into the Next Best Action framework
Communicate findings clearly to technical and executive audiences, and mentor other analysts and scientists.

The Role:
A True Problem Solver Were looking for a Senior DS who thrives on End-to-End ownership. You aren't just given a dataset; you identify the business opportunity, architect the mathematical solution, and write the high-quality, production-ready code that brings it to life. This is the ultimate "DS Candy Store" for those who love research but live for the adrenaline of seeing their code drive real revenue.
What Youll Do:
End-to-End Ownership: Own the entire lifecycle: from defining the business problem and KPI to deploying and monitoring the solution in production
High-Scale Architecture: Design and implement ML models & handling high-cardinality data at massive scale
Engineering Excellence: Write clean, modular, and scalable code. We believe great Data Science is built on a foundation of great Software Engineering
Strategic Leadership: Mentor the team through complex technical hurdles and contribute directly to our algorithmic roadmap.

Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of our companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across our company to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization.

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across all of our company.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build our company's next-generation data stack.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools
In this role you'll
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals.

Appdome's mission is to protect every mobile app in the world and the people who use them. We are the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps — with no SDKs, no coding, and no disruption to engineering cycles.
Our platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities, powered by deep learning models trained on a decade of mobile defense data and trillions of live threat events. From build time to runtime, Appdome's AI Agents help mobile brands detect, investigate, and respond to threats faster than ever — recognized as the best AI Platform for Cyber Resilience at RSA Conference 2026 for the second consecutive year. Leading financial, healthcare, m-commerce, and B2B brands rely on Appdome to secure over 50,000 mobile apps and protect more than 1 billion end users globally.
Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.
?About the Role
We are looking for a Data Assurance Engineer with strong experience in data validation, automation, analytics testing, and large-scale event pipeline quality.
This role is focused on ensuring the accuracy, stability, and reliability of data across our analytics and security event systems. The ideal candidate will be responsible for building automated validations, investigating data discrepancies, monitoring data quality, and working closely with engineering, data, and product teams.
Responsibilities

* Design, build, and maintain automated validation processes for large-scale event pipelines.
* Validate end-to-end data flows across ingestion, processing, storage, and dashboard layers.
* Create SQL-based validations to verify event counts, unique devices, metadata accuracy, schema
* consistency, latency, and data freshness.
* Investigate discrepancies between production systems, staging environments, data warehouses, object
* storage, and customer-facing dashboards.
* Monitor event volume, data latency, anomalies, spikes, drops, duplicates, and missing data.
* Build and maintain CI/CD validation jobs using tools such as Jenkins or GitLab CI.
* Create clear automated reports, dashboards, and email summaries for validation results.
* Work closely with backend engineers, data engineers, QA teams, and product stakeholders to identify,
* report, and validate fixes for data quality issues.
* Support performance and scalability testing for analytics dashboards, queries, and data pipelines.
* Help improve internal data assurance processes, data observability, and production monitoring.

We are looking for a Data Engineer to join our usage metering & billing platform team! with a strong background in writing ETLs and complicated data processing pipelines. Youre deeply familiar with modern data processing stack (especially Spark, Hadoop and Airflow), have a strong problem-solving attitude and, most importantly, youre passionate about understanding the business side of the platform. Our platform engineers have an end-to-end understanding of the data our products generate and the commercial models and data structures in which they fit.

What youll do:
Develop end-to-end ETLs and data infrastructure features from data processing logic to database choice and implementation through to API development.
Improve the scalability and performance of existing data pipelines.
Delve into existing pipelines and business logic, target weaknesses and add functionality.
Mentor, advise, and work collaboratively within the Biz Data & Dev group, with other development teams, and with all other business teams of the company.
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible.
Collaborate on software-oriented projects as needed, bridging data engineering expertise with backend development work in a cross-functional environment.