דרושים » דאטה » Data Analyst

We are seeking a Senior BI Engineer to serve as the primary interface and strategic analytics partner between Data Engineering / DWH teams, management, and business leaders. In this strategic role, you will work closely with leadership and business partners to translate business objectives into actionable data solutions, establish analytics standards and best practices, and lead experimentation across core business processes. You will also plan, prioritize, and manage analytics initiatives and roadmaps, ensuring the timely delivery of insights and solutions that drive informed decision-making across Marketing, Sales, Finance, Support, and Customer Success.

Key Responsibilities

Serve as the primary interface and analytics partner between Data Engineering / DWH teams and business stakeholders
Translate business needs into analytics requirements, specifications, roadmaps, and prioritized backlogs
Collaborate with Data Engineers on DWH requirements, data models, and pipelines
Plan, coordinate, and track analytics initiatives and projects to ensure timely delivery and alignment with business objectives
Support stakeholders in understanding, interpreting, and using ingested and production data
Define and own analytics standards, metrics, and best practices across the company
Design, execute, and analyze experiments to optimize core business processes
Define dashboard requirements and deliver impactful dashboards and insights
Work with Systems, Product, and R&D teams to map data sources, address data gaps, and improve data quality

We are looking for a GTM Strategic Analyst to partner closely with Sales, Marketing, Finance, Customer Success, and executive leadership to drive data-informed decisions across the go-to-market organization.
This is a high-impact individual contributor role, focused on solving complex business problems and shaping strategy - not building dashboards or data infrastructure.
You will work hands-on with data to analyze performance across the revenue lifecycle (pipeline, bookings, retention, efficiency), and translate insights into clear, actionable recommendations that influence planning, prioritization, and execution.
What Youll Do:
Partner with GTM and executive stakeholders to support strategic decisions and planning processes
Own end-to-end analyses: frame problems, explore data (SQL), and deliver clear recommendations
Analyze key GTM areas such as pipeline health, sales performance, marketing effectiveness, and growth drivers
Translate complex findings into concise, decision-ready narratives (presentations, summaries)
Proactively identify trends, risks, and opportunities to improve business performance
Work closely with the data team, leveraging existing datasets and models

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.

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.
Actively take part in building and maintaining our AI Driven-BI Agentic Architecture.
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.

Required Cyber Data Analyst
Description
We are redefining trust in blockchain through advanced, integrated security. Our on-chain security platform is trusted by leading Web3 companies-including Coinbase, MetaMask, Uniswap, Backpack, Stellar, and others-to detect, understand, and automatically prevent or minimize the impact of fraud, scams, hacks, and financial threats.
We are backed by top-tier global investors including Sequoia Capital, Ribbit Capital, and Cyberstarts-firms known for supporting the most innovative and influential companies in technology and cybersecurity.
As a Senior Data Analyst within our R&D team, you will shape how we understand data, uncover trends, and drive strategic decisions across. Working closely with cross-functional teams, you will turn complex datasets into actionable insights that directly influence our business growth and product direction.
Your Chain of Impact:
Identify, analyze, and interpret trends or patterns in complex datasets to uncover actionable insights.
Analyze large datasets to provide clear, impactful recommendations that support operational and strategic goals.
Develop scalable data processes and infrastructure to support internal stakeholders.
Build and maintain dashboards, reports, and KPIs to monitor and improve company performance.
Translate business questions into analytical models and craft compelling data visualizations that tell the story.
Partner with cross-functional teams to understand business needs and design data-driven solutions.

Were looking for a Senior BI Data Engineer to join our BI team and take end-to-end ownership of high-impact analytics foundations. This role sits at the core of how measures success, makes decisions, and scales - turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.
Youll design and evolve data models, pipelines, and the BI layer, work closely with Data Science and business stakeholders, and help raise the bar for analytics engineering across the company.
Hands-on experience using GenAI to improve analytics engineeing workflows, automate development processes, and increase delivery speed is a must for this role.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.
This might be for you if:
You enjoy owning data foundations end to end - from raw data to semantic layers
You like turning ambiguous business questions into clear, governed metrics
You care about data quality, performance, and trust at scale
You enjoy mentoring, setting standards, and leading by example
You actively leverage AI tools to improve development speed and analytical accuracy

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

As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.

Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.


Key Job Responsibilities and Duties:

Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.

Dealing with massive textual sources to train GenAI foundation models.

Solving issues with data and data pipelines, prioritizing based on customer impact.

End-to-end ownership of data quality in our core datasets and data pipelines.

Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.

Providing tools that improve Data Quality company-wide, specifically for ML scientists.

Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.

Acting as an intermediary for problems, with both technical and non-technical audiences.

Promote and drive impactful and innovative engineering solutions.

Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.

Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.


Key Job Responsibilities and Duties:

Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.

Dealing with massive textual sources to train GenAI foundation models.

Solving issues with data and data pipelines, prioritizing based on customer impact.

End-to-end ownership of data quality in our core datasets and data pipelines.

Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.

Providing tools that improve Data Quality company-wide, specifically for ML scientists.

Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.

Acting as an intermediary for problems, with both technical and non-technical audiences.

Promote and drive impactful and innovative engineering solutions.

Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

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