We're looking for an experienced Data Analyst to join our growing Data team and help shape one of the core functions at our company.
This isn't a traditional BI or Product Analytics role. You'll work across engineering, data science, product, research, and customer-facing teams to understand complex data from enterprise environments, transform it into a consistent data model, and generate insights that directly power our product and customer experience.
You'll wear multiple hats-from researching new data sources and designing scalable data models to supporting customer onboarding, surfacing meaningful insights, and helping define how our data platform evolves as the company grows. This also means getting hands-on in the codebase: you'll regularly modify logic in production system components, not just analyze data from the outside.
If you're someone who enjoys turning messy data into clear decisions, thrives in ambiguous environments, and wants to build the foundations of a data function from the ground up, we'd love to meet you.
What You'll Do
Research and evaluate new customer data sources, APIs, and integrations, understanding what data is available, how reliable it is, and how it can create value.
Analyze large, complex datasets to identify patterns, anomalies, and actionable insights that improve our product and customer outcomes.
Design and evolve our company's data models, creating a unified language across data coming from multiple integrations and systems.
Partner closely with Engineering and Data Science teams to define schemas, data structures, and scalable modeling approaches.
Build and modify logic in system components as part of regular delivery, not just spec it for someone else to build.
Support customer onboarding by validating incoming data, identifying issues, and ensuring customers receive meaningful insights from day one.
Deliver customer-facing analyses, reports, and recommendations while working against real customer deadlines.
Help define the foundations of our company's data function by evaluating tools, methodologies, and best practices that will scale with the company.
Work closely with Product to ensure product decisions are informed by data and grounded in real customer behavior.
Collaborate on AI-powered capabilities by helping define the data, signals, and requirements that enable intelligent product features and autonomous workflows.

we are looking for a Data Analyst.
As a Data Analyst, you'll play a key role in shaping product strategy and business decisions by turning complex data into actionable insights. You'll partner with Product, Engineering, and customer-facing teams to build scalable analytics solutions, define success metrics, and uncover opportunities that drive impact across our platform
What youll do:
Own the product analytics domain for key Autofleet products and strategic initiatives, with a focus on user behavior and product engagement.
Design, build, and own our product analytics infrastructure (event tracking, taxonomy, instrumentation) from the ground up, primarily using Mixpanel.
Define and maintain a clean, scalable event-tracking taxonomy in partnership with Engineering and Product.
Analyze large-scale product and behavioral datasets to identify trends, opportunities, and business insights.
Design, build, and maintain dashboards and reporting solutions using Mixpanel and other modern BI tools.
Develop automated data pipelines and analytical workflows using Python and Airflow.
Partner closely with Product Managers to define KPIs and metrics (activation, retention, funnels, engagement), measure success, and support product decision-making.
Work with customer-facing teams to provide insights and occasionally participate in customer discussions and presentations.
Build internal tools and processes that improve data accessibility and operational efficiency.
Translate complex data findings into clear recommendations for both technical and non-technical stakeholders.

we are building the future of AI-powered software development. Our tools help engineering teams write better code, ship with more confidence, and move faster - without sacrificing quality. From intelligent code review to AI-driven test generation, our company sits at the intersection of developer tooling and cutting-edge AI. Were a fast-growing, product-led company trusted by thousands of developers and engineering teams worldwide.
Were looking for a Data Analyst to join our growing data team and help make analytics a core part of how we build. Youll work on the product-usage side of an AI product that thousands of developers rely on - understanding how teams adopt AI code review, which features drive value, and where we can make the experience better. Its a product-focused role at heart, reaching into business, operational, and cost metrics too, with room to shape how we work as the team grows.
Be the go-to analyst for the product team - drive product analytics day to day: how developers use our AI features, plus retention and conversion funnels
Turn raw product and usage data into clear, consistent metrics the team can trust
Build and maintain the modeled data layer, so metrics live in one place and analysis is repeatable rather than rebuilt each time
Build and maintain dashboards so teams can self-serve answers
Run deep-dive analysis to surface opportunities and support product decisions and experimentation
Extend into business and operational KPIs - conversion, churn, segmentation, customer value - and cost / unit-economics
Take analyses from problem definition through to clear recommendations, not just reports.

we are looking for a Data Analyst
Responsibilities

Own and define key product, business, and customer KPIs across the company
Analyze usage, funnels, monetization, and customer behavior to identify growth opportunities and friction points
Build and maintain dashboards and reports that give teams clear, reliable visibility into performance
Partner with Product and Business to evaluate new features, initiatives, and experiments, and measure their impact
Drive customer value by delivering external-facing data solutions, actionable insights, and industry benchmarks to empower data-informed decision-making.
Work closely with engineering and data stakeholders to improve data quality, structure, and accessibility
Help foster a data-driven culture by making insights understandable and actionable for non-technical stakeholders

We are currently seeking an experienced Product analyst to join our new and growing Data & Analytics team in Tel Aviv!

As a key member of our core Data & Analytics team, you will work closely with decision-makers within the Product department. In this role, you will drive analysis into our business health and stand at the forefront of identifying actionable trends, challenges, and opportunities.

With limitless potential, you will help shape and prioritize our strategic decisions using data-driven insights and thoughtful, passionate recommendations. This isnt your typical analyst role, it is a highly visible position where you will help scale our operational cadence and grow into an influential leader within the company.

** This position is temporary for a duration of 8 months, with an option to extend

What You'll Own
Work closely with our Product Managers to monitor, measure, and drive clarity around product performance across both self-serve (B2C/PLG) and enterprise (B2B) user journeys.

Analyze complex, customer-reported data issues and collaborate closely with R&D and Product Managers to resolve them.

Build and maintain the companys core reports and dashboards, balancing your focus across analytics, strategy, process, and infrastructure.

Define and track KPIs for various departments, equipping them with the tools and insights needed to take data-backed action.

Partner with Marketing to analyze acquisition, activation, and conversion funnels, measuring campaign and channel effectiveness end-to-end.

Bring new perspectives and innovative ideas to the table, and continuously measure their impact on the business.

Lead the way to consume data through a single, unified source of truth.

We're looking for a Senior Data Product Manager to drive the strategy, architecture, and execution of the data that power the Retail Intelligence products suite, eCommerce analytics product.

This role sits at the intersection of data infrastructure and customer value - you'll own the datasets, pipelines, and methodologies that help leading brands and retailers make confident decisions about their commerce assets.


What youll experience on this team?

Work with top talent across data, engineering and product teams.
Ship AI-powered capabilities iteratively, improving with every release.
Work with latest technology in an ever-evolving work environment
Operate with a startup mindset: move fast, think big, and build long-term value for customers.
Have direct impact on how customers make business decisions
What youll do as a Senior Data Product Manager?

Own the vision, roadmap, and delivery of the datasets that underpin Retail Intelligence, from eCommerce traffic and conversion data to product-level insights and category benchmarks.
Lead AI integration into internal processes and core features that speed customer decisions.
Define and track data quality metrics (completeness, coverage, freshness, accuracy) and establish validation, logging, and governance frameworks.
Lead modularization of data structures to enable scalability, and continuous improvement.
Stay close to customers and the market through ongoing research and interviews.
Partner with engineering, data science, design, sales, and marketing to deliver and drive adoption.

Required AI Data Engineer
About the role:
We're building the intelligence layer that lets everyone ask hard questions of our data and get trustworthy answers - in plain language, in seconds. As AI Data Engineer, you own the semantic and AI-native surface of our Snowflake platform: the governed semantic layer that defines "what a metric means," the Cortex Agents that let business users query it conversationally, and the infrastructure that keeps all of it fast, reliable, and ready to scale.
This is a builder-owner role. You'll ship the semantic models, wire up the agents, and set the standard for how analysts across the company work with data. You'll also lead the Data Analyst guild - the connective tissue that keeps our hub-and-spoke analytics model coherent as it grows.
If you're excited by the space where data engineering, LLM tooling, and analytics governance meet, this role sits right in the middle of it.
What youll Own:
Snowflake semantic layer - Own the semantic layer end-to-end as the single source of truth for metrics; design semantic models, enforce naming standards, and ensure consistent metric definitions across dashboards and AI agents.
Cortex Agents - Design and deploy conversational AI agents using Cortex Analyst and Cortex Search; tune for accuracy and safety, expose through multiple surfaces (Snowflake Intelligence, Streamlit, MCP), and build evaluation harnesses to maintain quality at scale.
Data craft (Analytics guild) - Co-lead the technical track of the Analytics guild; set SQL and modeling standards, run technical enablement and code reviews, and serve as the technical authority for analysts.
Scaling data infrastructure - Improve performance, reliability, cost efficiency, and governance across the dbt/Airflow/Airbyte/Snowflake stack as data volume and query load grow; optimize warehouse sizing, medallion layers, and ingestion pipelines.
What you'll do day to day:
Model and maintain semantic views that power both dashboards and AI agents, keeping definitions versioned, tested, and certified.
Build, evaluate, and iterate on Cortex Agents - including retrieval quality, guardrails, and observability.
Extend and optimize dbt models, Airflow DAGs, and Airbyte connectors across bronze/silver/gold layers.
Partner with GTM, Finance, CS, and Product stakeholders to translate business questions into governed, reusable data assets.
Run the Data Analyst guild: standards, reviews, enablement, and tooling.
Own data quality, lineage, and cost monitoring across the Snowflake platform.
Expose data and agents through Streamlit apps, BI tools (Omni), and MCP servers for internal AI workflows.

We are looking for a strong Data Engineer to be part of one of our most strategic initiatives - building the context graph that powers our AI-SOC platform. Our team is building the context layer behind our AI Agents, transforming raw customer data into meaningful, normalized context that enables smarter autonomous security decisions.

This is a unique opportunity to join a brand-new, small, senior team with high ownership, strong product influence, and the chance to build foundational AI infrastructure from the ground up.

What Youll Be Doing:
Think like a product person - collaborate with stakeholders and consumers to design meaningful data models and continuously validate them against real customer data.
Run POCs work end to end - connect a new data source, ingest and normalize it, correlate entities across systems, and demonstrate the value.
Do the analysis that shapes the model - profile new data, measure coverage and accuracy, and find the gaps that matter to the product.
Integrate identity, endpoint, and security data sources - learn how each system exposes its data and turn it into reliable, consistent models.
Build and own scalable data pipelines, transforming raw data into clean, normalized, and well-tested models using Python, SQL, and dbt.

We are looking for an experienced and visionary Data Engineer to help design, build, and scale our BI platform.
In this role, you will be responsible for developing our data analytics platform - enabling scalable data pipelines and robust data modeling to support real-time and batch analytics to provide insights that serve both business intelligence and product needs.
You will be part of the R&D team, collaborating closely with engineers, analysts, and product managers to deliver a modern data architecture that supports internal dashboards and future-facing operational analytics.
If you enjoy turning raw data into powerful insights and owning the full data lifecycle, this role is for you!
Responsibilities:
Take full ownership of the design and implementation of a scalable and efficient BI data infrastructure, ensuring high performance, reliability, and security.
Design and architect data products, from ingestion to transformation, modeling, storage, and access.
Build and maintain ETL/ELT pipelines, batch and real-time, to support analytics, reporting, and product integrations.
Establish and enforce best practices for data quality, lineage, observability, and governance to ensure accuracy and consistency.
Integrate modern tools and frameworks such as Airflow, Databricks, Power BI, and streaming platforms.
Collaborate cross-functional with product, engineering, and analytics teams to translate business needs into data infrastructure.
Promote a data-driven culture - be an advocate for data-driven decision-making across the company by empowering stakeholders with reliable and self-service data access.

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.
Key responsibilities:
Lead a team of data scientists, data engineers and product analysts
Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation
Drive excellence, code quality, and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences
Ensure AI solutions are safe, scalable, observable, and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy, UX, and business impact
Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring, evaluation, and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes.