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We're seeking a Data Engineer to architect and develop sophisticated data solutions using advanced Spark, PySpark, Databricks and EMR implementations in our mission to transform the cyber-security breach readiness and response market.

Join us in crafting cutting-edge solutions for the cyber world using Spark/PySpark ETLs and data flow processes. Dive into the realm of multi-Cloud environments while collaborating closely with investigators to fine-tune PySpark performance. Harness the power of top-notch technologies like Databricks to elevate our technical projects, scaling them for efficiency. Embrace innovation as you research and implement new techniques. Evolve with us as a key member of the R&D team.

Technical Impact:
Design and implement complex data processing architectures for cloud security analysis.
Optimize and scale critical PySpark workflows across multi-cloud environments.
Develop innovative solutions for processing and analyzing massive security datasets.
Drive technical excellence through sophisticated ETL implementations.
Contribute to architectural decisions and technical direction.

Core Responsibilities:
Build robust, scalable data pipelines for security event processing.
Optimize performance of large-scale PySpark operations.
Implement advanced data solutions using Databricks and cloud-native technologies.
Research and prototype new data processing methodologies.
Provide technical guidance and best practices for data engineering initiatives.

Location: Tel Aviv, IL.
Hybrid work environment.

Were looking for a Data Engineer to join our BI Team within the R&D department. This role is all about building and maintaining robust data pipelines and enabling data-driven decision-making across all departments.

Responsibilities:
Develop and maintain ETL processes and data pipelines to ensure smooth, accurate data flow.
Designed, built, and managed Airflow DAGs to orchestrate complex data workflows and ensure reliable execution of ETL and analytics tasks
Design and optimize relational databases, including conceptual and physical data modeling (ERD), schema design, and performance tuning to support scalable analytics and business applications.
Collaborate with cross-functional teams to translate business needs into technical solutions.
Build and maintain automation processes powered by algorithms to optimize workflows for reducing manual effort.
Build and maintain custom data scripts for integrations with brand and publisher partners
Support data visualization efforts through BI tools.
Gain in-depth understanding of discrepancy processes across departments and improve data accuracy.

We are building next-generation GenAI 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 Pythonic data pipeline 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.
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 GenAI Protection.

Our Data Science team leads data-motivated decisions across Waze's core functional areas, including the waze map and map editor, advanced guidance and voices, growth and strategy, user communications, and more. The team members are embedded within the waze development squads. We define data requirements and analytics strategies, execute experiments, deliver in-depth analyses and provide actionable recommendations. The teams contribution is crucial for the effective development and safe landing of the new waze features and help guiding the overall product strategy.
We are responsible for the research and development of advanced experimentation and causal analysis infrastructures to measure, understand and attribute features impact. We also own a comprehensive data warehouse, providing essential dashboards and analytics tools, including Gen-AI agents, to empower both Data Scientists and stakeholders throughout the organization.
Responsibilities
Develop and implement measurement methodologies and evaluation frameworks. Assess the performance, accuracy and groundedness of AI Agents, including the automated generation of synthetic training and evaluation data.
Work with various teams including software developers, data engineers and product managers, to define the requirements and implement Gen-AI models and solutions to drive innovation.
Translate technical concepts and investigative findings into clear, actionable insights for both technical and non-technical stakeholders.
Lead the design, development and deployment of Generative AI Agents for conversational driving-related experiences and scaling the ingestion, annotation and utilization of user generated contect and geospatial data feeds.

Were looking for a Data Engineer to join our team and help shape a modern, scalable data platform. Youll work with cutting-edge AWS technologies, Spark, and Iceberg to build pipelines that keep our data reliable, discoverable, and ready for analytics.

Whats the Job?
Design and maintain scalable data pipelines on AWS (EMR, S3, Glue, Iceberg).
Transform raw, semi-structured data into analytics-ready datasets using Spark.
Automate schema management, validation, and quality checks.
Optimize performance and costs with smart partitioning, tuning, and monitoring.
Research and evaluate new technologies, proposing solutions that improve scalability and efficiency.
Plan and execute complex data projects with foresight and attention to long-term maintainability.
Collaborate with engineers, analysts, and stakeholders to deliver trusted data for reporting and dashboards.
Contribute to CI/CD practices, testing, and automation.

The Performance Marketing Analytics team is seeking a highly skilled Senior Data platform Engineer to establish, operate, and maintain our dedicated Performance Marketing Data Mart within the Snowflake Cloud Data Platform. This is a critical, high-autonomy role responsible for the end-to-end data lifecycle, ensuring data quality, operational excellence, and governance within the new environment. This role will directly enable the Performance Marketing team's vision for data-driven marketing and increased ownership of our analytical infrastructure
Responsibilities
Snowflake Environment Management
Administer the Snowflake account (roles, permissions, cost monitoring, performance tuning).
Implement best practices for security, PII handling, and data governance.
Act as the subject matter expert for Snowflake within the team.
DevOps & Model Engineering
Establish and manage the development and production environments.
Maintain CI/CD pipeline using GitLab to automate the build, test, and deployment process.
Implement normal engineering practices such as code testing and commit reviews to prevent tech debt.
Data Operations & Reliability
Monitor pipeline executions to ensure timely, accurate, and reliable data.
Set up alerting, incident management, and SLAs for marketing data operations.
Troubleshoot and resolve platform incidents quickly to minimize business disruption.
Tooling & Integration
Support the integration of BI, monitoring, and orchestration tools
Evaluate and implement observability and logging solutions for platform reliability.
Governance & Compliance
Ensure alignment with Entain data governance and compliance policies.
Document operational procedures, platform configurations, and security controls.
Act as the team liaison with procurement, infrastructure, and security teams for platform-related topics.
Collaboration & Enablement
Work closely with BI, analysts and data engineers, ensuring the platform supports their evolving needs.
Provide guidance on best practices for query optimization, cost efficiency, and secure data access.

We are seeking a Senior Data Analyst position to join the BI Team, with a passion for technology, to solve unique problems within our measurements. Our team solves many challenges in turning raw data into accurate signals and extracting insights to improve the products. Appropriate candidates have an understanding of multiple components across the big data stack: large-scale data analysis, data quality, statistics, and visualization. If you are the kind of researcher who's focused on results and a quick learner, this role is for you. This position is located in our Tel Aviv office.
Responsibilities
Function as the data authority in the Monetization domain - performing ad-hoc research and analysis on the company's rich data to support unique and strategic business questions.
Define, analyze, and monitor KPIs and OKR metrics to continually improve company products.
Analyze large, complex data sets to address strategic and operational business questions.
Build dashboards and visualizations to answer key questions for the company's in-house various teams, specifically for the Monetization Team.
Perform qualitative, quantitative, and statistical analysis.
True passion for understanding data and finding Insights.
Provide actionable recommendations and conclusions from data to shape features and future product road maps.

We are looking for an exceptional Big Data Engineer to join our R&D team. This is a unique opportunity for a recent graduate or early-career engineer to enter the world of Big Data. You will work alongside the best engineers and scientists in the industry to develop systems that process and analyze data from around the digital world.
So what will you be doing all day?
Learn and Build: Assist in the design and implementation of high-scale systems using a variety of technologies, mentored by senior engineers.
Collaborate: Work in a data research team alongside data engineers, data scientists, and data analysts to tackle data challenges.
Optimize: Help improve the existing infrastructure of code and data pipelines and learn how to identify and eliminate bottlenecks.
Innovate: Experiment with various technologies in the domain of Machine Learning and big data processing.
Monitor: Assist in maintaining monitoring infrastructure to ensure smooth data ingestion and calculation.

Required Data Scientist Team Manager
A day-to-day role as a Team Manager includes:
Managing a multidisciplinary team of data engineers, data scientists, and data analysts.
Leading the development of advanced and creative solutions for complex technical challenges in areas like big data and machine learning.
Collaborating closely with data extraction, platform, and product teams.
Communicating with business stakeholders and gathering feedback from customers.
Hiring new team members and developing the groups structure.
Playing a crucial role in shaping product strategy within a startup-like environment.
Day-to-day, the team you will lead will:
Develop statistical and machine learning algorithms on large-scale data to estimate metrics, create features, and deliver insights.
Own end-to-end data processes and pipelines, from research and proof of concept to production.
Collaborate with product and R&D teams to plan and deliver best-in-class digital insights.
Design, validate, and monitor ongoing processes to ensure quality and reliability.
Identify, analyze, and monitor new raw data sources as needed.

We are looking for a highly motivated and talented Marketing Data Analyst to join our Analytics team and contribute to our marketing organization's strategic decision-making process.
As a Marketing Data Analyst, you will work closely with members of the marketing organization to drive impact, value, and insights using data and play a key role in our growth.
What does a Marketing Data Analyst mean?
Collaborate closely with members of the marketing & product organizations to leverage data for strategic decision-making.
Design and build dashboards to monitor business KPIs, ensuring data hygiene and integrity.
Develop models, targets, and tracking reports to measure the effectiveness of our marketing efforts.
Identify new growth opportunities and foster a data-driven culture within the marketing organization.
Communicate your findings and recommendations to stakeholders in a clear and compelling manner.
Collaborate with data engineers to integrate new data sources, enhancing our systems.

Were looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D.
Why is this role so important?
We are a data-focused company, and data is the heart of our business.
As a big data engineer developer, you will work at the very core of the company, designing and implementing complex high scale systems to retrieve and analyze data from millions of digital users.
Your role as a big data engineer will give you the opportunity to use the most cutting-edge technologies and best practices to solve complex technical problems while demonstrating technical leadership.
So, what will you be doing all day?
Your role as part of the R&D team means your daily responsibilities may include:
Design and implement complex high scale systems using a large variety of technologies.
You will work in a data research team alongside other data engineers, data scientists and data analysts. Together you will tackle complex data challenges and bring new solutions and algorithms to production.
Contribute and improve the existing infrastructure of code and data pipelines, constantly exploring new technologies and eliminating bottlenecks.
You will experiment with various technologies in the domain of Machine Learning and big data processing.
You will work on a monitoring infrastructure for our data pipelines to ensure smooth and reliable data ingestion and calculation.

Were looking for an Analytics Engineer to join our team and play a key role in shaping how data drives our product and business decisions.
This role is perfect for someone who enjoys working at the intersection of data, product, and strategy. While Product Analysts focus on turning data into insights, youll focus on building the strong data foundations that make those insights possible. You wont just run queries; you will design the data architecture and own the "source of truth" tables that power our strategic decision-making.
Youll work closely with our Growth and Solutions teams, helping them move faster and smarter by making sure the data behind Generative AI, Data-as-a-Service (DaaS), and advanced product models is clear, reliable, and easy to use. Your work will have a direct impact on how we build, scale, and innovate our products.
What Youll Do
Define the Source of Truth: Take raw, complex data and transform it into clean, well-structured tables that Product Analysts and Business Leads can use for high-stakes decision-making.
Translate Strategy into Logic: Work with Product, Growth, and Solutions leads to turn abstract concepts (like "Activation," "Retention," or "Feature Adoption") into precise SQL definitions and automated datasets.
Enable High-Tech Initiatives: Partner with our AI and DaaS specialists to ensure they have the structured data foundations they need to build models and external data products.
Optimize for Usability: Ensure our data is not just "there," but easy to use. You will design the data logic that powers our most important product dashboards and growth funnels.
Maintain Data Integrity: Act as the guardian of our metrics. You will ensure that the numbers used across our product and business reports are consistent, reliable, and logical.

We are looking for a Senior Data Platform Engineer to design, build, and scale next-generation data platform, the backbone powering our AI-driven insights.
This role sits at the intersection of data engineering, infrastructure, and MLOps, owning the architecture and reliability of our data ecosystem end-to-end.
Youll work closely with data scientists,r&d teams, analysts to create a robust platform that supports varying use cases, complex ingestion, and AI-powered analytics.
Responsibilities:
Architect and evolve a scalable, cloud-native data platform that supports batch, streaming, analytics, and AI/LLM workloads across R&D.
Help define and implement standards for how data is modeled, stored, governed, and accessed
Design and build data lakes and data warehouses
Develop and maintain complex, reliable, and observable data pipelines
Implement data quality, validation, and monitoring frameworks
Collaborate with ML and data science teams to connect AI/LLM workloads to production data pipelines, enabling RAG, embeddings, and feature engineering flows.
Manage and optimize relational and non-relational datastores (Postgres, Elasticsearch, vector DBs, graph DBs).
Build internal tools and self-service capabilities that enable teams to easily ingest, transform, and consume data.
Contribute to data observability, governance, documentation, and platform visibility
Drive strong engineering practices
Evaluate and integrate emerging technologies that enhance scalability, reliability, and AI integration in the platform.

we are looking for a Senior Data Scientist.
As an Applied Researcher, you will play a central role in advancing our AI capabilities -fine-tuning and optimizing large language models to extract legal insights and power intelligent decision-making at scale. Youll explore new model architectures, training paradigms, and evaluation methods to push research from experimentation to impactful, production-ready innovation.
Youll collaborate closely with data scientists, engineers, and domain experts to design and validate research prototypes, integrating cutting-edge methods such as model distillation, retrieval-augmented generation (RAG), and knowledge-graphbased reasoning.
Responsibilities:
Design and evaluate new model architectures, training objectives, and loss functions that enhance generalization and domain adaptation.
Research and innovate in areas such as model compression, knowledge distillation, and retrieval-augmented generation (RAG) to improve inference efficiency and interpretability.
Publish and present innovative findings internally and externally to advance the organizations leadership in applied AI research.
Collaborate cross-functionally with engineering, product, and data science teams to transition research prototypes into scalable production systems
Drive measurable impact by translating research innovations into deployable solutions that improve model performance, scalability, and user outcomes.
Contribute to the research community through publications, open-source contributions, or collaborations, showcasing thought leadership in LLM fine-tuning and applied AI innovation.