דרושים » דאטה » Head of Analytics & AI Delivery

We are looking for an experienced Data Engineering Team Leader.

In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.

A day in the life and how youll make an impact:

Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.

Were looking for an Analytics Engineer to join our team and play a key role in shaping how data drives our product and business decisions.
This role is perfect for someone who enjoys working at the intersection of data, product, and strategy. While Product Analysts focus on turning data into insights, youll focus on building the strong data foundations that make those insights possible. You wont just run queries; you will design the data architecture and own the "source of truth" tables that power our strategic decision-making.
Youll work closely with our Growth and Solutions teams, helping them move faster and smarter by making sure the data behind Generative AI, Data-as-a-Service (DaaS), and advanced product models is clear, reliable, and easy to use. Your work will have a direct impact on how we build, scale, and innovate our products.
What Youll Do:
Define the Source of Truth: Take raw, complex data and transform it into clean, well-structured tables that Product Analysts and Business Leads can use for high-stakes decision-making.
Translate Strategy into Logic: Work with Product, Growth, and Solutions leads to turn abstract concepts (like "Activation," "Retention," or "Feature Adoption") into precise SQL definitions and automated datasets.
Enable High-Tech Initiatives: Partner with our AI and DaaS specialists to ensure they have the structured data foundations they need to build models and external data products.
Optimize for Usability: Ensure our data is not just "there," but easy to use. You will design the data logic that powers our most important product dashboards and growth funnels.
Maintain Data Integrity: Act as the guardian of our metrics. You will ensure that the numbers used across our product and business reports are consistent, reliable, and logical.

We are looking for an Experienced Data Engineer to join our marketing team and take end-to-end ownership of our data platform and production data pipelines. In this role, you will be responsible for building robust, scalable, and observable data systems that power analytics, reporting, and downstream business use cases. You will work deeply hands-on with data infrastructure, modeling, and orchestration, and act as a key technical partner to Marketing, Sales Product and Business and Finance teams.
This role suits someone who enjoys working close to the metal, designing systems that scale, and solving ambiguous data problems in a dynamic startup environment. You will play a critical role in shaping how data flows through the company, setting engineering standards, and ensuring data is trustworthy, performant, and ready for growth.
What You'll Do:
Design, build, and maintain scalable, reliable data pipelines and data warehouse architectures to support analytics and business intelligence needs.
Own the end-to-end ETL/ELT processes - ingesting data from internal and external sources, transforming it, and making it analytics-ready.
Model and optimize data structures (fact tables, dimensions, semantic layers) to support performant querying and reporting.
Ensure high standards of data quality, integrity, observability, and reliability across all data assets.
Partner closely with Analytics, Product, Marketing, and Finance teams to understand data requirements and deliver robust data solutions.
Implement monitoring, alerting, and testing frameworks to proactively identify data issues.
Optimize warehouse performance and cost efficiency (query optimization, partitioning, clustering, etc.).
Identify gaps in data collection and work with engineering teams to improve instrumentation and data availability.
Support experimentation and analytics use cases by enabling clean, trustworthy datasets for A/B testing and analysis.
Document data models, pipelines, and best practices to support scale and knowledge sharing.

Required Data Engineer, Product Analytics
As a Data Engineer, you will shape the future of people-facing and business-facing products we build across our entire family of applications. Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.
In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.
You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining us, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.
Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.
Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Engineer, Product Analytics Responsibilities
Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts.

Required Data Engineer II - GenAI
20718
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
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.

We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.
This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutions-including the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.
🔧 What Youll Do
Architecture & Strategy
Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.
Engineering & Delivery
Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.
Leadership & Collaboration
Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization

Required Senior Data Engineer I - GenAI Foundation Models
21679
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
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.

Required Data Engineer, Product Analytics
As a Data Engineer, you will shape the future of people-facing and business-facing products we build across our entire family of applications. Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.
In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.
You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining us, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.
Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.
Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Engineer, Product Analytics Responsibilities
Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights visually in a meaningful way
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts.

Were seeking an experienced and skilled Data and AI Infra Engineer to join our Data Infrastructure team and drive the companys data capabilities at scale.
As the company is fast growing, the mission of the data and AI infrastructure team is to ensure the company can manage data at scale efficiently and seamlessly through robust and reliable data infrastructure.
A day in the life and how youll make an impact:
As a Senior Engineer, you are required to independently lead the design, development, and optimization of our data infrastructure, collaborating closely with software engineers, data scientists, data engineers, and other key stakeholders. You are expected to own critical initiatives, influence architectural decisions, and mentor engineers to foster a high-performing team
You will:
Lead the design and development of scalable, reliable, and secure data storage, processing, and access systems.
Define and drive best practices for CI/CD processes, ensuring seamless deployment and automation of data services.
Oversee and optimize our machine learning platform for training, releasing, serving, and monitoring models in production.
Own and develop the company-wide LLM infrastructure, enabling teams to efficiently build and deploy projects leveraging LLM capabilities.
Own the company's feature store, ensuring high-quality, reusable, and consistent features for ML and analytics use cases.
Architect and implement real-time event processing and data enrichment solutions, empowering teams with high-quality, real-time insights.
Partner with cross-functional teams to integrate data and machine learning models into products and services.
Ensure that our data systems are compliant with the data governance requirements of our customers and industry best practices.
Mentor and guide engineers, fostering a culture of innovation, knowledge sharing, and continuous improvement.