דרושים » דאטה » Data & AI Product Engineer

We're looking for a Full-Cycle Data Engineer to join our Data & AI team and own the flow from product data sources → modeling → dashboards → insights. You'll partner with product managers, engineers, and AI teams to turn raw product data into reliable analytics infrastructure that drives decisions across the company - from individual feature bets to CEO- and CFO-level questions.
This is an end-to-end role: you'll take data products from ideation through engineering, analytics, and production deployment.
Responsibilities
Pipelines & infrastructure:
Design, build, and deploy scalable data pipelines from product and system sources in production, using Python and orchestrators like Airflow.
Work with distributed query engines such as BigQuery or Athena, with strong SQL throughout.
Build and maintain semantic data models for large-scale operational systems and data lakes, manually or with tooling like dbt.
Improve the end-to-end analytics stack, from ingestion to visualization, and collaborate with engineering on event tracking and instrumentation.
Ensure data quality, consistency, and reliability across the stack.
Analytics & reporting:
Build and maintain dashboards and reporting layers in tools like Looker or Metabase, optimized for performance, usability, and clarity
Create self-serve analytics so product and business stakeholders can answer their own questions
Support product experimentation: A/B testing, funnel analysis, feature adoption
Partnership & insight:
Translate ambiguous questions from product leads, the CEO, the CFO, and others into clear metrics, KPIs, and analytical models
Surface trends in usage and user behavior that influence the product roadmap and feature prioritization
Provide ad-hoc analysis and strategic reporting for leadership.

were looking for a Head of Analytics to define and elevate how analytics is practiced across the organization.

This is a senior individual contributor role with broad organizational influence. Beyond delivering insights, youll define how success is measured, establish analytical standards and methodologies, and help teams across Product, Growth, Marketing, Sales Operations, and Content make better decisions with data.

Youll serve as a trusted advisor to senior stakeholders, raise the analytical maturity of the organization, and help drive the next generation of AI-powered analytics.

What Youll Do:

Promote Data-Driven Decision Making
Partner with Product, Growth, Marketing, Sales Operations, and Content teams to understand business challenges and enable better decision-making.
Define KPI frameworks and measurement strategies that align with business goals.
Translate complex business questions into clear analytical approaches and actionable recommendations.
Act as a trusted advisor to stakeholders, challenging assumptions and influencing decisions through data.

Build Analytics Excellence
Establish analytical methodologies, standards, and best practices across the organization.
Lead the companys approach to experimentation, KPI definition, and performance measurement.
Mentor analysts and help raise the overall analytical capabilities of the team.
Promote a culture where data-driven decision-making becomes the default.

Drive Product, Growth & Subscription Analytics
Partner with teams across the customer lifecycle, from acquisition and activation through conversion, retention, and monetization.
Analyze user behavior, subscription performance, pricing initiatives, and product changes to uncover growth opportunities.
Connect analytical findings to clear business actions and measurable outcomes.

Shape the Future of AI in Analytics
Leverage AI tools to accelerate analysis, insight generation, and decision-making.
Help design AI-powered analytical workflows and data analysis agents.
Continuously identify opportunities to improve how analytics creates business value through AI.

Improve Analytics Infrastructure
Identify gaps in tracking, data quality, measurement, and reporting.
Partner with data and engineering teams to improve data availability, reliability, and accessibility.
Drive the development of dashboards, alerts, and scalable self-service analytics capabilities.
Ensure business teams can confidently access and interpret the data they need.

As our company continues to scale, were looking for a Product Data Analyst to join our Product team. In this role, youll blend strong analytical skills with operational execution to help our product and go-to-market teams make data-informed decisions. About 70% of your time will be spent analyzing product and customer data, building dashboards, and delivering insights that will shape the future of our product. The remaining 30% will focus on supporting our data operations - ensuring our data processes, tools, and reporting cadences run efficiently, implementing best practices.

Youll sit directly within the Product organization, collaborating closely with Product Managers, Designers, and Engineers to improve how we use data across a growing suite of B2B SaaS products and within our organization.

Responsibilities
Analytics
Analyze product usage and customer behavior across multiple SaaS products to uncover insights that guide roadmap priorities and growth opportunities.
Build and maintain dashboards and reports in Snowflake, Redash, Metabase, and Mixpanel using SQL to support Product, GTM, and leadership teams.
Define and track key metrics such as activation, retention, adoption, ARR growth, and engagement.
Run ad-hoc analyses to answer business questions and support experiments or feature evaluations.

Data Operations
Collaborate with Engineering and Data teams to enhance analytics setup and data workflows.
Partner with Engineering teams to ensure clean data instrumentation, event tracking, best practices for data, and measurement implementation across product features.
Maintain and improve data quality processes, pipeline documentation, and operational standards to support reliable decision-making.

Director, Business Intelligence & AI to join our Business Applications organization. This is a senior individual contributor role with a director title and light team leadership (5 people), sitting at the intersection of data strategy, architecture, and execution. You'll own the data foundation that powers our company's most critical business decisions - from GTM and revenue analytics to operational intelligence across the organization.

You'll report to the VP of Business Applications and work closely with stakeholders across Finance, Sales, Marketing, Customer Support, Product, R&D, and HR to ensure our data assets are trustworthy, scalable, and increasingly AI-ready



What will you do?

Architecting the data foundation that makes it possible for business users to ask questions in plain English and get trusted, real-time answers.
Define and execute a strategy to migrate from traditional BI (dashboards, scheduled reports) toward AI-powered, natural language interfaces for business intelligence
Architect the data layer that enables LLM-based querying - including semantic layers, vector stores, knowledge graphs, and metadata enrichment - so that AI agents can reliably reason over company data
Design and own a scalable, AI-ready data architecture - warehouse/lakehouse structure, semantic layer, and data contracts - that supports both analytical and AI/ML workloads
Build robust data modeling foundations (clean entities, clear metrics definitions, consistent taxonomies) that LLMs can reason over accurately
Serve as a trusted advisor to business leaders across GTM, Customer Success, Finance, and Product - proactively engaging them to understand their decision-making needs
Translate ambiguous business questions ("why is churn spiking in the mid-market?") into well-defined data problems, and then into scalable, AI-powered solutions
Build strong relationships with stakeholders at all levels - from individual analysts to VP and C-suite - and maintain a prioritized roadmap that reflects real business value

We're looking for a Product Data Analyst to help us find the opportunities hiding in our data and turn them into real product improvements.
You'll be part of the Analytics team, embedded in product decisions from early question to final recommendation. You will be tackling analytical questions, monitoring the metrics that matter, and surfacing insights that actually change how we build
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:
Collaborate with Analytics, Product, and Data teams to sharpen business decisions.
Initiate analyses and generate reports for feature tracking, experiments, and product health monitoring
Design A/B tests across our flows and processes to build better products
Analyze data using Snowflake, Python, and other platforms
Present key findings to stakeholders across the company, turning data into clear, actionable direction
Map new data domains and identify signals that push our product forward

we are looking for a Data AI Engineer.
Join our global Data team, which partners closely with Product, Engineering, and Business stakeholders to power data-driven decision making and AI-driven products across . The team operates in a fast-paced, high-growth environment, building AI solutions, data foundations, and analytical frameworks that directly influence product strategy and customer outcomes.
What youll do
Design and build LLM-powered systems that directly improve product capabilities and customer experience - enabling Product, Engineering, and Business teams to make faster, smarter, data-driven decisions at scale
Evaluate and quantify the business impact of AI initiatives through rigorous experimentation, benchmarking, and model evaluation to continuously optimize LLM performance
Continuously monitor, refine, and evolve AI models and solutions - iterating on prompt engineering and deployment practices to keep pace with rapidly advancing capabilities and shifting business needs.
Leverage AI-assisted development tools (e.g., Cursor, Claude Code) to accelerate delivery speed and engineering velocity across the team
Analyze large-scale datasets to surface strategic insights, define and track critical KPIs, and translate analytical findings into actionable product and business recommendations.

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

We're looking for a Senior Data Infrastructure Engineer to help us build the data foundation that powers everything does. You'll be joining the Data Platform team in TLV, working on the infrastructure that ingests, processes, and governs data across a growing stack of products, customers, and microservices - structured and unstructured, streaming and batch. The work you do here sits at the core of how every team makes decisions.
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:
Design and implement data solutions for all application requirements in a distributed microservices environment
Build ingestion layers and a data lake using streaming ETLs and Change Data Capture
Implement large-scale batch and streaming pipelines with modern data processing frameworks
Build pipelines and scheduling infrastructures that other teams rely on every day
Ensure data quality, compliance, and governance across entire data platform
Help shape data-mesh concepts that empower other teams to leverage data independently
Partner with Data Engineers, ML Engineers, Data Scientists, BI Engineers, and Product Managers to move fast and build right

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 analytics domain for key products and strategic initiatives.
Analyze large-scale operational and product datasets to identify trends, opportunities, and business insights.
Design, build, and maintain dashboards and reporting solutions using modern BI tools.
Develop automated data pipelines and analytical workflows using Python and Airflow.
Partner closely with Product Managers to define KPIs, 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.
Utilize modern AI-assisted development tools (such as Claude Code) to accelerate analysis, automation, and development workflows.
Translate complex data findings into clear recommendations for both technical and non-technical stakeholders.