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We're seeking an outstanding and passionate Data Platform Engineer to join our growing R&D team.
You will work in an energetic startup environment following Agile concepts and methodologies. Joining the company at this unique and exciting stage in our growth journey creates an exceptional opportunity to take part in shaping our data infrastructure at the forefront of Fintech and AI.
What you'll do:
Design, build, and maintain scalable data pipelines and ETL processes for our financial data platform
Develop and optimize data infrastructure to support real-time analytics and reporting
Implement data governance, security, and privacy controls to ensure data quality and compliance
Create and maintain documentation for data platforms and processes
Collaborate with data scientists and analysts to deliver actionable insights to our customers
Troubleshoot and resolve data infrastructure issues efficiently
Monitor system performance and implement optimizations
Stay current with emerging technologies and implement innovative solutions
Tech stack: AWS Serverless, Python, Airflow, Airbyte, Temporal, PostgreSQL, Snowflake, Kubernetes, Terraform, Docker.

Rakuten Viber is one of the most popular and downloaded apps in the world. Working with us means influencing hundreds of millions of users and shaping the journey toward becoming a true super-app. Our mission is to make people’s lives easier by enabling meaningful connections — from special moments with friends and family, to building businesses and pursuing passions. We’re looking for a Senior Data Analyst who combines strong technical skills with a strategic mindset and curiosity for how data drives user experience and growth in social mobile apps. You’ll partner closely with product, engineering, and marketing teams to turn data into clear insights and measurable business impact. If you’re passionate about uncovering insights, leveraging data and AI for smarter, faster results, and driving decisions at scale; we’d love to hear from you!

Responsibilities:

* Identify opportunities for improvement through data analysis aligned with company strategy.?
* Partner cross-functionally to translate data findings into actionable product and business decisions.?
* Design, run, and analyze A/B tests to evaluate product changes and user experience optimizations.?
* Build, automate, and maintain dashboards and reports to track platform health, user behavior, and key trends.?
* Communicate findings clearly to stakeholders, influencing both tactical and strategic decisions.?
* Leverage AI and automation tools to accelerate analytical workflows and uncover deeper insights.

Advantages:

* Background in statistics, causal inference, or experimentation frameworks.?
* Experience mentoring analysts or leading analytical projects.?
* A deep interest in social, communication, or engagement-driven apps.

We are looking for a Senior Data Engineer to join our growing team of data experts. As a Senior Data Engineer, you will be responsible for designing, implementing, and optimizing data pipeline flows within the system. You will support our data scientists with the implementation of the relevant data flows based on the data scientists features design and construct complex rules to detect money laundering activity.

The ideal candidate has experience in building data pipelines and data transformations and enjoys optimizing data flows and building them from the ground up. They must be self-directed and comfortable supporting multiple production implementations for various use cases.



Responsibilities

Implement and maintain data pipeline flows in production within the system
Design and implement solution-based data flows for specific use cases, enabling the applicability of implementations within the product
Building a Machine Learning data pipeline
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
Work with product, R&D, data, and analytics experts to strive for greater functionality in our systems
Train customer data scientists and engineers to maintain and amend data pipelines within the product
Travel to customer locations both domestically and abroad
Build and manage technical relationships with customers and partners

We are looking for a Data & Analytics Engineer to join our Customer Performance team and help shape the foundation of our data platform.
You will own the data layer, evolve our BI semantic layer on a modern BI platform, and enable teams across the company to access and trust their data. Working closely with analysts and stakeholders in Operations, Product, R&D, and Customer Success, youll turn complex data into insights that drive performance and customer value.
A day in the life
Build and expand our analytics data stack
Design and maintain curated data models that power self-service analytics and dashboards
Develop and own the BI semantic layer on a modern BI platform
Collaborate with analysts to define core metrics, KPIs, and shared business logic
Partner with Operations, R&D, Product, and Customer Success teams to translate business questions into scalable data solutions
Ensure data quality, observability, and documentation across datasets and pipelines
Support complex investigations and ad-hoc analyses that drive customer and operational excellence.

To ensure our live deployments deliver maximum impact, were looking for a hands-on, insights-driven Senior Data Analyst to lead performance tracking and optimization for our product and customers.
As Senior Data Analyst, youll be responsible for analyzing production data to monitor store performance, improve current operations, and provide insights that shape our future roadmap. Youll also structure and manage how operational data is collected, aggregated, and analyzed, ensuring it delivers actionable value across teams.
This role sits within the Customer Performance team our group responsible for ensuring our deployments perform at their best and deliver measurable value. Youll collaborate closely with Operations, Product, R&D, Customer Success, and our retail partners.
A day in the life
Analyze production data from live stores to assess system performance and customer behavior.
Track and report on agreed KPIs with retail partners, ensuring we deliver against operational commitments.
Manage and structure operational data defining what is included in analysis and how it is aggregated.
Collaborate with Data Engineering to analyze, maintain, and improve ETL workflows and data pipelines, ensuring data is accurate, timely, and accessible for analysis.
Build dashboards to surface insights internally and for retailer-facing teams.
Provide insights that inform both current operational improvements and our product roadmap.
Liaise with cross-functional teams (Operations, Product, R&D, Customer Success) to proactively suggest system enhancements.
Communicate complex KPIs, concepts, and insights in a clear, structured, and compelling way, tailored to technical and non-technical audiences.

Required Senior Data Scientist
Tel Aviv Full-time.
Responsibilities
Conduct hands-on research and development of cutting-edge models
Take research projects from ideation to deployment and production
Work closely with domain experts and the engineering department to improve and create new innovative solutions.
Help define the AI product roadmap.

Required Data Engineer - AI Infra Group
Tel Aviv Full-time
The Job
We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world data platforms. You'll architect and ship our streaming lake-house and data platform, turning billions of raw threat signals into high-impact, self-serve insights that protect countries in real time all while building on top-of-the-line technologies, such as Iceberg, Flink, Paimon, Fluss, LanceDB, ClickHouse and more.
Responsibilities
Design and maintain agentic data pipelines that adapt dynamically to new sources, schemas, and AI-driven tasks
Build self-serve data systems that allow teams to explore, transform, and analyze data with minimal engineering effort
Develop modular, event-based pipelines across AWS environments, combining cloud flexibility with custom open frameworks
Automate ingestion, enrichment, and fusion of cybersecurity data including logs, configs, and CTI streams
Collaborate closely with AI engineers and researchers to operationalize LLM and agent pipelines within the CLM ecosystem
Implement observability, lineage, and data validation to ensure reliability and traceability
Scale systems to handle complex, high-volume data while maintaining adaptability and performance
Own the data layer end-to-end including architecture, documentation, and governance.

We are looking for an experienced BI Data Engineer to join our Data team within the Information Systems group.
In this role, you will be responsible for building and maintaining scalable, high-quality data pipelines, models, and infrastructure that support business operations across the entire company, with a primary focus on GTM domains.
You will take ownership of core data architecture components, ensuring data consistency, reliability, and accessibility across all analytical and operational use cases.
Your work will include designing data models, orchestrating transformations, developing internal data applications, and ensuring that business processes are accurately represented in the data.
This role requires a combination of deep technical expertise and strong understanding of business operations.
You will collaborate closely with analysts, domain experts, and engineering teams to translate complex business processes into robust, scalable data solutions. If you are passionate about data architecture, building end-to-end data systems, and solving complex engineering challenges that directly impact the business wed love to meet you!
Key Responsibilities:
Design, develop, and maintain end-to-end data pipelines, ensuring scalability, reliability, and performance.
Build, optimize, and evolve core data models and semantic layers that serve as the organizations single source of truth.
Implement robust ETL/ELT workflows using Snowflake, dbt, Rivery, and Python.
Develop internal data applications and automation tools to support advanced analytics and operational needs.
Ensure high data quality through monitoring, validation frameworks, and governance best practices.
Improve and standardize data modeling practices, naming conventions, and architectural guidelines.
Continuously evaluate and adopt new technologies, features, and tooling across the data engineering stack.
Collaborate with cross-functional stakeholders to deeply understand business processes and translate them into scalable technical solutions.

We are looking for a Data Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance.

We're looking for a Senior Business Analyst to lead the data domain within our Working Capital Business unit - a high-impact, fast-moving team that operates like a startup within a global company.
This is a unique opportunity for a hands-on, strategic thinker to take full ownership of our data domain: from defining and executing our data strategy, to building advanced risk models and scalable infrastructure - while leading the data domain in a matrixed structure that includes a business analyst and a data engineer.
The ideal candidate brings a strong analytical mindset, experience in data modeling, and a proven ability to turn complex datasets into actionable insights that shape business strategy. They also possess the skills to design and build scalable data infrastructure, along with strong teamwork and leadership capabilities in a cross-functional environment.
What youll do:
Own and lead the data domain within the Working Capital unit, including analytics, modeling, and infrastructure.
Design, develop, and maintain our risk scoring model - a core component of the product used to assess credit risk.
Develop, refine, and maintain dashboards, reports, and visualizations to monitor key KPIs.
Conduct in-depth analysis to uncover trends and deliver strategic, actionable insights for all business domains (Risk, Growth, and Ops).
Guide and mentor analysts, fostering a high standard of analytical thinking and execution.
Partner with cross-functional teams (RevOps, Marketing, finance, operations, etc.) to enhance the data infrastructure supporting the Working Capital business.

We are seeking a seasoned and execution driven VP, head of data platform to lead all the R&D tracks of the Data and Analytics organization in our company. This role focuses on leading a complex data engineering organization at scale, driving delivery, operational excellence and cross-company enablement through world-class data platforms and tools.
This leader will serve as the engineering owner of our data platform, managing multiple data infra, data engineering and BI development teams, overseeing extensive resources, and ensuring the delivery of high-quality, scalable, and reliable data products and services. This position requires a strong technical background combined with exceptional leadership, strategic thinking, and cross-functional collaboration skills.
He will also act as a key stakeholder in defining the architecture and strategic direction of our data infrastructure, pipelines, AI/ML infra and platforms to support the company's rapid growth and evolving business needs.
What youll do: 
Lead and manage the entire data platform, including:
Real-Time Data & Streaming Infrastructure: Introduce and engineer robust data streaming infrastructures (e.g., using Kafka, Pub/Sub, Dataflow) to enable near-real-time data ingestion and scalable low-latency data serving, unlocking advanced analytics and critical use cases.
Data engineering teams responsible for the data ingestion, transformation and delivery pipelines
BI infra and development teams owning the cross-company consumption layer, including BI tools, BI data layers and dashboards
Serve as the operational and delivery lead across the data platform, ensuring strong project execution, roadmap alignment and measurable business impact
Data Engineering & Architecture Oversight: Lead the design, development, and evolution of scalable data platforms, encompassing data lakes, data warehouses, and advanced data products, ensuring they meet performance, reliability, and business requirements.
Operational Excellence & Reliability: Establish and drive engineering operational excellence processes across data engineering, significantly improving data quality, availability, and system reliability. Implement frameworks for proactive monitoring, alerting, and incident management, reducing major incidents and ensuring continuous visibility into data flows.
Advanced Data Observability: Integrate and leverage cutting-edge data observability solutions (e.g., Monte Carlo) to provide comprehensive visibility into data pipelines, enabling proactive detection and resolution of anomalies.
Cross-functional Collaboration & Stakeholder Management: Collaborate extensively with product, analytics, business, and infrastructure teams to align data strategies with overarching business priorities, ensuring the delivery of high-quality data products that meet diverse user needs.
Innovation & Technology Adoption: Stay abreast of the latest data, cloud, and AI trends, driving the evaluation and adoption of modern cloud-native technologies to continuously improve platform capabilities and future-proof the ecosystem.
Leadership & Team Growth: Lead, mentor, and grow a large team of data engineers, fostering a culture of technical excellence, continuous learning, and agile methodologies. Oversee budget management and drive talent development within the team.
Data Governance & Quality: Oversee the implementation of standards for data quality, data integrity tools, governance, privacy, and regulatory compliance across the data ecosystem

We are looking for an experienced Senior Data Scientist to join our rapidly growing data science team, focusing on creating ML-driven prediction and anomaly detection models. As a Senior Data Scientist, you will lead the analysis of large (often massive) datasets, develop models and algorithms to meet customer needs. You will be working closely with other data scientists, data engineers, product managers and domain experts to improve our automotive purpose-built data management platform, focusing on vehicle quality, cybersecurity and API security use cases.
As a Senior Data Scientist, youll play a pivotal role in driving innovation and shaping the future of ML-based solutions in automotive quality and cyber security. Youll work on challenging datasets, develop advanced models, and see your work integrated into impactful, real-world applications.
Your work will directly enhance the safety and quality of advanced automotive systems and cybersecurity solutions. We prioritize talent development, offering you opportunities to learn, innovate, and grow in a collaborative environment.
This role is full-time and is Herzliya, Israel based.
Responsibilities
Conduct in-depth research on large and diverse automotive live streaming tabular datasets, preprocess the data, as well as extract and present key insights
Search and craft indicative features that will enhance the value of ML models
Explore, design and deploy cutting-edge ML models or algorithms solutions for prediction purposes and anomaly detection
Collaborate closely with domain experts and peers to research and implement models and algorithm flows that best fit requirements
Partner with our data engineering and development teams to devise innovative solutions for productization
Encourage collaboration and knowledge-sharing within the data science team.

Required Senior Data Engineer
Description
Join our core platform engineering team, developing our AI-powered automotive data management platform.
We are developing the next generation data-driven products for the Automotive industry, focusing on cybersecurity (XDR) and vehicle quality. our products monitor and secure millions of vehicles worldwide and help automakers leverage connected vehicle data to deliver cyber resilience, safety, customer satisfaction and increase brand loyalty.
Our Data Engineering & Data Science Group leads the development of our Iceberg-based data platform, including data lake, query engine, and ML-Ops tools, serving as a solid AI-ready foundation for all our products.
At the core of our Engineering Team, you will build and operate scalable, production-grade customer-facing data and ML platform components, focusing on reliability and performance.
Technological background and focus: Iceberg, Trino, Prefect, GitHub Actions, Kubernetes, JupyterHub, MLflow, dbt
This role is full-time and is Herzliya, Israel based.
Responsibilities
Design, build, and maintain scalable data pipelines to ingest and transform batch data on our data lake, enabling analytics and ML with strong data quality, governance, observability, and CI/CD.
Build and expand our foundational data infrastructure, including our data lake, analytics engine, and batch processing frameworks.
Create robust infrastructure to enable automated pipelines that will ingest and process data into our analytical platforms, leveraging open-source, cloud-agnostic frameworks and toolsets.
Develop and maintain our data lake layouts and architectures for efficient data access and advanced analytics.
Build our ML platform and automate the ML lifecycle.
Drive business-wide ML projects from an engineering perspective.
Develop and manage orchestration tools, governance tools, data discovery tools, and more.
Work with other team members of the engineering group, including data architects, data analysts, and data scientists, to provide solutions using a use case-based approach that drives the construction of technical data flows.