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.

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

Were looking for an experienced Data Engineer to join our DataWarehouse team in TLV.
In this role, you will play a pivotal role in the Data Platform organization, leading the design, development, and maintenance of our data warehouse. In your day-to-day, youll work on data models and Backend BI solutions that empower stakeholders across the company and contribute to informed decision-making processes all while leveraging your extensive experience in business intelligence.
This is an excellent opportunity to be part of establishing Lemonades state-of-the-art data stack, implementing cutting-edge technologies in a cloud environment.
In this role youll:
Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into the semantic layer
Develop processes to enforce schema evaluation, cover anomaly detection, and monitor data completeness and freshness
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency
Implement best practices for data warehouse and database performance tuning
Conduct thorough testing of data applications and implement robust validation processes
Collaborate with Data Infra Engineers, Developers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers

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.

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.

We act as the central nervous system for engineering, enabling platform teams to unify their stack and expose it as a governed layer through golden paths for developers and AI agents.
By combining rich engineering context, workflows, and actions, we help organizations transition from manual processes to autonomous, AI-assisted engineering workflows while maintaining control and accountability.
As a product-led company, we believe in building world-class platforms that fundamentally shape how modern engineering organizations operate.
What youll do:
Lead the design and development of scalable and efficient data lake solutions that account for high-volume data coming from a large number of sources both pre-determined and custom.
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs.
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into a data lake that will serve our company's users.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Collaborate with cross-functional teams (product, analytics, and R&D) to enhance our company's data solutions.
Who youll work with:
Youll be joining a collaborative and dynamic team of talented and experienced developers where creativity and innovation thrive.
You'll closely collaborate with our dedicated Product Managers and Designers, working hand in hand to bring our developer portal product to life.
Additionally, you will have the opportunity to work closely with our customers and engage with our product community. Your insights and interactions with them will play an important role to ensure we deliver the best product possible.
Together, we'll continue to empower platform engineers and developers worldwide, providing them with the tools they need to create seamless and robust developer portals. Join us in our mission to revolutionize the developer experience!

Required Senior Data Engineer
What youll do:
Lead the design and development of scalable and efficient data lake solutions that account for high-volume data coming from a large number of sources both pre-determined and custom.
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs.
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into a data lake that will serve our users.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Collaborate with cross-functional teams (product, analytics, and R&D) to enhance our data solutions.
Who youll work with:
Youll be joining a collaborative and dynamic team of talented and experienced developers where creativity and innovation thrive.
You'll closely collaborate with our dedicated Product Managers and Designers, working hand in hand to bring our developer portal product to life.
Additionally, you will have the opportunity to work closely with our customers and engage with our product community. Your insights and interactions with them will play an important role to ensure we deliver the best product possible.
Together, we'll continue to empower platform engineers and developers worldwide, providing them with the tools they need to create seamless and robust developer portals. Join us in our mission to revolutionize the developer experience!

Were looking for a Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Data Science Team Manager in the R&D.
Why is this role so important at our company?
we are a data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create and support a complex data model pipeline that helps analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data engineer in the Datalabs team, you will work on the very core of the company. Part of your role will be to create processes that help turn raw data into usable metrics and leverage AI models and statistical algorithms to support out-of-the-box requests from customers who want custom data labs. The Datalabs departments business-oriented nature also means you will be supporting a team of analysts and data scientists who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class data labs.
So, what will you be doing all day?
Building and maintaining our big-data pipelines
Take a major part in designing and implementing complex high-scale systems using a large variety of technologies
Be part of a team with smart and motivated engineers, and data scientists, to collaborate on the planning, development, and maintenance of our products
Implement solutions in the AWS cloud environment, and work in Databricks with PySpark.

We are seeking a Senior Data Engineer to join our Data team,
The Data team develops and maintains the infrastructure for internal data and product analytics,
In this role, you will design and manage complex data pipelines and work closely with data analysts,
software engineers, and other stakeholders to continuously improve data processes and solutions.
What you will do:
Architect, develop, and maintain scalable, end-to-end data pipelines from diverse data sources
Monitor and maintain data systems, ensuring uptime, reliability, and stability
Provide technical expertise and insights to shape overall data strategy and best practices
Strong team player with excellent communication skills.

we are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will play a key role in shaping and driving our analytics data pipelines and solutions to empower business insights and decisions. Collaborating with a variety of stakeholders, you will design, develop, and optimize scalable, high-performance data analytics infrastructures using modern tools and technologies. Your work will ensure data is accurate, timely, and actionable for critical decision-making.
Key Responsibilities:
Lead the design, development, and maintenance of robust data pipelines and ETL processes, handling diverse structured and unstructured data sources.
Collaborate with data analysts, data scientists, product engineers and product managers to deliver impactful data solutions.
Architect and maintain the infrastructure for ingesting, processing, and managing data in the analytics data warehouse.
Develop and optimize analytics-oriented data models to support business decision-making.
Champion data quality, consistency, and governance across the analytics layer.