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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.
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 next-generation data stack.
We believe three things matter for every role: 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

Were looking for an experienced Data Engineer to join our DataWarehouse team in TLV.
In this role, you will play a pivotal role in the Data Platform organization, leading the design, development, and maintenance of our data warehouse. In your day-to-day, youll work on data models and Backend BI solutions that empower stakeholders across the company and contribute to informed decision-making processes all while leveraging your extensive experience in business intelligence.
This is an excellent opportunity to be part of establishing our state-of-the-art data stack, implementing cutting-edge technologies in a cloud environment.
We believe three things matter for every role: 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:
Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into the semantic layer
Develop processes to enforce schema evaluation, cover anomaly detection, and monitor data completeness and freshness
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency
Implement best practices for data warehouse and database performance tuning
Conduct thorough testing of data applications and implement robust validation processes
Collaborate with Data Infra Engineers, Developers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers

We're looking for a Senior Business Analyst to help build the technical foundation that powers our cross-sell growth and revenue measurement across all DTC products.
You'll join our Analytics team in Tel Aviv to create the data infrastructure that turns customer journeys into measurable expansion opportunities. As we scale across insurance lines, this role bridges the gap between raw data and the automated systems that drive our AI-powered revenue growth.
We believe three things matter for every role: 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:
Facilitate cross-sell initiatives by building data frameworks (identity resolution, behavioral tagging) that help Company Leads and Product teams identify and measure opportunities across car, pet, and renters products
Automate revenue measurement systems by taking existing MMM, incrementality, and attribution models and building the ETL logic layer that makes them work together autonomously
Drive MarTech and revenue automation through DBT models that ensure seamless data flows between our warehouse and platforms like Google Ads and AppsFlyer
Contribute to partnership systems by supporting the technical rebuild of our partnership data infrastructure for accurate tracking and attribution of third-party leads
Collaborate with Data Platform teams to ensure revenue requirements are reflected in our data stack, acting as the technical bridge between raw data lakes and business analytics
Enable revenue squads by building shared DBT models and centralized tracking systems that Car, Pet, and Renters teams need to hit their DTC goals
Build scalable frameworks that turn analytical concepts into production-grade, automated pipelines within our data warehouse,

Required Product Data Analytics Lead
What youre applying for:
We're transforming insurance with AI, and we need a Product Data Analytics Lead who's ready to shape how millions of people experience insurance through data-driven insights!
You'll lead our Growth Product Analytics team - the people who turn user behavior into actionable product opportunities. You'll lead a team of analysts while working closely with Product Managers and other business stakeholders to turn user behavior into actionable insights.
As part of our broader Analytics organization, you'll focus specifically on product analytics while collaborating with other Data and Analytics teams across the company.
We believe three things matter for every role: 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 product analytics team, while fostering a culture of analytical excellence.
Gain deep understanding of our users behavior and translate complex behavioral patterns into clear, actionable recommendations
Prioritize your team's focus and mentor them to deliver insights with high impact on product decisions.
Partner with Product, Engineering, and business teams to prioritize work that moves the needle
Stay hands-on with strategic analyses while orchestrating your team's delivery on high-impact projects
Guide your team to uncover opportunities that others miss - the insights that become our competitive advantage
Help raise the analytics bar across while contributing to our AI-driven initiatives.

Were looking for a talented AI research team lead for the Data Science group, to help us develop advanced AI solutions that will empower impactful projects across. The Data Science group leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product, optimize processes, and deliver personalized experiences.
Lead a team of AI researchers
Manage and conduct advanced hands-on research projects that will impact 250M+ users
Leverage the latest advancements in LLM customization, multimodal models, knowledge representation, and conversational AI
Build horizontal AI capabilities to be used across
Collaborate with other internal departments to drive impactful data-driven projects.

you will be part of our company rem department. our road experience management (rem) is an end-to-end mapping and localization engine. this process leverages advanced algorithms, massive parallelization, and Big Data technologies, creating a highly complex system that demands both a deep understanding of the map creation workflow and strong technical expertise. were looking for a senior data engineer to lead the architecture and development of large-scale, production-grade data pipelines supporting ml inference systems. what will your job look like:
architect and own end-to-end data pipelines for large-scale model inference
design high-throughput, scalable data streaming to the cloud
integrate data conversion into data collection and inference pipelines
drive performance, scalability, and reliability across distributed systems
partner with ml, platform, and infrastructure teams

join our company outstanding team and contribute to our legacy of innovation in the senior quality data analyst engineer role! at our company, we are dedicated to pushing the boundaries of pioneering technology. the senior data analyst engineer will lead advanced data analysis and optimization for networking products in mass production. the successful candidate will leverage technical expertise and manufacturing experience to deliver actionable insights from complex datasets.
what you'll be doing:
develop automated dashboards, kpis, and reports to monitor production health, yield, TEST results, quality trends and customers satisfaction indicators
identify and drive root cause analysis of anomalies or degradations in key metrics (yield loss, reliability issues, field returns, customers complaints).
collaborate with cross-functional teams in different time zones (such as manufacturing, TEST engineering, r&d, quality and sales).

we are looking for an expert data engineer to build and evolve the data backbone for our r&d telemetry and performance analytics ecosystem. responsibilities include processing raw, large quantities of data from live systems at the cluster level: hardware, communication units, software, and efficiency indicators. youll be part of a fast paced r&d organization, where system behavior, schemas, and requirements evolve constantly. your mission is to develop flexible, reliable, and scalable data handling pipelines that can adapt to rapid change and deliver clean, trusted data for engineers and researchers.
what youll be doing:
build flexible data ingestion and transformation frameworks that can easily handle evolving schemas and changing data contracts
develop and maintain ETL /elt workflows for refining, enriching, and classifying raw data into analytics-ready form
collaborate with r&d, hardware, DevOps, ml engineers, data scientists and performance analysts to ensure accurate data collection from Embedded systems, firmware, and performance tools
automate schema detection, versioning, and validation to ensure smooth evolution of data structures over time
maintain data quality and reliability standards, including tagging, metadata management, and lineage tracking
enable self-service analytics by providing curated datasets, apis, and databricks notebooks

We are looking for a Data Operations Team Lead to lead and scale our data operations function. This role sits at the intersection of data, algorithms, and operations, and is critical to the success of our computer vision and AI models.
You will lead a distributed team responsible for data collection, annotation, quality control, and delivery, while working closely with Algorithm teams to understand model needs, prioritize requests, and ensure reliable, high-quality data pipelines.
This is a hands-on leadership role - you will manage people and processes, but also actively design, build, and improve data workflows.
About The Role
Lead and manage the Data Operations team, including annotation teams in Israel and a large remote team in India
Serve as the primary interface between Data Operations and Algorithm teams: understand model requirements, prioritize tasks, and plan data delivery
Own end-to-end data workflows, from model improvement needs through data definition, annotation guidelines, execution, and delivery
Ensure high data quality through close monitoring, validation, troubleshooting, and root-cause analysis
Design and maintain clear annotation guidelines, documentation, and training materials
Closely manage remote annotation teams, including weekly syncs, hands-on oversight, and deadline management
Own and operate the annotation pipeline using industry tools (e.g., CVAT)
Monitor progress, track performance, and continuously improve efficiency and quality
Own annotation budgets, monthly reporting, and validation of hours and outputs
Evaluate, benchmark, and implement new tools and processes in the data and annotation domain
Work hands-on with scripts, AI tools, and monitoring systems as needed to support data quality and operations.

We are looking for an Analytics Engineer to join Orcas next-generation big data platform. In this role, you will play a significant part in implementing algorithms and AI-driven logic into our product, helping notify customers about ocean dangers and making maritime voyages safer worldwide.

You will play a central role in building the semantic tables and business logic layer that power advanced product capabilities, real-time notifications, and data-driven decision-making across our platform. Working closely with the Data Science team, you will define high-impact features for their models and integrate algorithms directly into the semantic layer.

This is a temporary position (Maternity leave replacement)

What Youll Do

Design and implement business logic and semantic tables that serve as the foundation for advanced platform features.
Build robust, scalable services that generate real-time notifications for hundreds of ships and fleet managers worldwide.
Deliver high-quality data products that serve operational systems, algorithms, and human-facing applications.
Quickly learn Orcas maritime domain and turn complex data into reliable semantic tables that power product features
Collaborate closely with data scientists, product teams, and engineers to embed algorithms and AI capabilities into production systems.
Be a pivotal contributor in a highly professional, impact-driven data team.

Welcome to Chargeflow Chargeflow is building the operating system for chargeback management. We help merchants automatically fight and recover disputed payments, reducing revenue loss and operational overhead. Our platform processes large volumes of payment and dispute data across merchants, payment processors, and financial systems. As Chargeflow scales its platform and customer base, data becomes one of the company’s most strategic assets - powering better products, smarter decisions, and operational efficiency.
Who We're Looking For - The Dream Maker We are looking for a Head of Data Analytics to build and lead the company’s data platform and data strategy. The Head of Data will own Chargeflow’s entire data platform, research, and data strategy This includes building the data infrastructure that powers the company, establishing reliable company-wide metrics, enabling data-driven decision making, and turning Chargeflow’s dispute and payments data into a long-term product advantage. This is a foundational leadership role responsible for making data a core capability across the organization. The Head of Data Analytics will work closely with Product, Engineering, Operations, and Leadership to ensure data becomes a central part of how the company builds products and runs the business. ?Your Arena ?Data Platform and Architecture - Design and lead the development of Chargeflow’s modern data infrastructure:
* Building scalable data pipelines across product, payments, disputes, and internal systems
* Developing a centralized data warehouse as the company’s single source of truth
* Ensuring data quality, reliability, and observability
* Establishing data governance and best practices Company Metrics and Decision Intelligence - Define and standardize the core metrics used across the company:
* Establishing a consistent metrics framework across product, revenue, and operations
* Building dashboards used by leadership and operational teams
* Ensuring reliable and accessible reporting across the organization
* Supporting data-driven decision making at the leadership level Product Data and Insights - Partner with Product and Engineering to leverage Chargeflow’s unique dispute and payment data:
* Identifying patterns and insights across disputes and recovery performance
* Enabling data-driven product development
* Supporting predictive capabilities and automation in dispute management
* Helping build product features powered by data insights Operational Intelligence - Provide visibility and insights into dispute operations and business performance:
* Building operational analytics dashboards
* Supporting forecasting and capacity planning
* Identifying automation opportunities
* Improving operational performance through data insights Building the Data Organization - Build and lead the company’s data team:
* Hiring and managing data engineers, analytics engineers, and analysts
* Establishing strong data culture and best practices
* Enabling teams across the company to use data effectively
* Ensuring data privacy, security, and governance standards What Success Looks Like - Within the first 12–18 months:
* Chargeflow operates from a trusted company-wide data platform
* Leadership and teams rely on consistent and reliable metrics
* Product teams leverage dispute data to build data-powered features
* Operational performance becomes clearly measurable and optimized
* A strong Data organization is established and growing

Responsibilities
Design, build, and maintain scalable ETL/ELT pipelines to integrate data from diverse sources, optimizing for performance and cost efficiency.
Leverage Databricks and other modern data platforms to manage, transform, and process data
Collaborate with software teams to understand data needs and ensure data solutions meet business requirements.
Optimize data processing workflows for performance and scalability.