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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 aspectsensuring 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 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 aspectsensuring 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 Analyst to help ensure the quality, completeness, and integrity of our foundational data. Youll work closely with data engineers, product managers, and operations teams to monitor pipelines, evaluate new data sources, design performance metrics, and derive insights that improve our entity models and customer outputs.
This role is ideal for a highly analytical and independent thinker who enjoys working with complex data ecosystems and translating messy real-world data into actionable insights.
RESPONSIBILITIES
Data Quality & Metrics
Define and maintain KPIs and quality metrics for POI and chain data accuracy, coverage, and freshness.
Monitor large-scale ingestion and enrichment pipelines, identifying anomalies, data drifts, or source inconsistencies.
Operational Analytics
Design dashboards and tools to track data health, system performance, and SLA compliance.
Provide visibility into the performance of automated systems and manual processes across the Foundation domain.
Cross-functional Collaboration
Work with engineers to validate and optimize merge, enrichment, and geocoding logic.
Partner with product and operations to assess the impact of data changes on downstream systems and customer-facing products.
Exploration & Research
Evaluate new data providers, test hypotheses about data behaviors, and contribute to decision-making for third-party integrations.
Develop data-driven recommendations to improve POI modeling and chain linkage accuracy.

Required Backend Data Engineer
As part of the role you will have the opportunity to:
Build end-to-end development of data infrastructure features, scalable data processing, database interaction and integration with CI/CD.
Take part in expanding our core data platform solutions, build new pipelines from scratch that ingest and process data at scale.
Work across a rich stack of technologies from Apache Kafka, Apache Storm, NoSQL, and relational databases.
Analyze and optimize performance, scalability, and stability of our product environments.
Work closely with the data-science team to implement production grade pipelines based on AI research.

Required Data Team Lead
As part of your role you will have the opportunity to:
Lead, mentor, and manage a team of experienced Data/Backend Engineers responsible for designing, building, and maintaining data infrastructure and data-driven applications
Oversee the planning and execution of the development cycle (e.g., sprints), ensuring timely and high-quality delivery
Define, build, and align the Data team roadmap with the company's product vision and overall R&D strategy
Analyze and optimize performance, scalability, and stability of Data team services
Collaborate effectively with other R&D teams on cross-functional projects and shared infrastructure
Take ownership of production incidents related to the Data domain, ensuring clear communication and effective coordination
Manage team performance and growth through regular 1:1 meetings, constructive feedback, periodic performance reviews, and comprehensive annual evaluations.

We are looking for an experienced and visionary Data Platform Engineer to help design, build and scale our BI platform from the ground up.

In this role, you will be responsible for building the foundations of our data analytics platform enabling scalable data pipelines and robust data modeling to support real-time and batch analytics, ML models and business 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 architecting from scratch, 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.

Lead the design and architecture of the data platform from integration 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, dbt, Databricks, Power BI, and streaming platforms.

Collaborate cross-functionally 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.

We are seeking a seasoned and strategic Head of BI to lead our Business Intelligence group.
In this pivotal role, you will be responsible for overseeing the full BI stackfrom data infrastructure and pipelines to analytics and reportingwhile managing a team of data engineers and analysts.
You will drive the design and execution of our data strategy, ensure delivery of trusted insights across the organization, and lead the team responsible for building and maintaining our data platform and analytics capabilities. This is a hands-on leadership role requiring a balance of technical depth, managerial experience, and strategic thinking.Responsibilities
What Youll Be Doing:
Lead, mentor, and scale a cross-functional team of BI Analysts and Data Engineers.
Own and evolve our data warehouse architecture, ensuring integrity, scalability, and performance (Snowflake preferred).
Oversee the design and development of ETL/ELT pipelines and semantic data models using tools such as dbt, Python, and Airflow.
Collaborate with senior stakeholders to align business goals with data priorities, translating requirements into scalable solutions.
Define and implement best practices across the entire BI lifecycle: data ingestion, transformation, modeling, visualization, and governance.
Deliver robust, actionable dashboards and insights that drive key business decisions and KPIs.

Were looking for a sharp Senior Product Data Analyst whos infinitely curious when it comes to leveraging data to solve product and business problems.

Youll be a part of the Analytics team and will spend your day-to-day tackling analytical questions and monitoring metrics. In order to succeed, youll need to demonstrate strong capabilities at modeling complex data, uncovering patterns, and delivering data-driven insights.

In this role youll:
Collaborate with members of the Analytics, Product, and Data teams to improve business decisions using data

Conduct A/B testing on our flow and processes in order to build state-of-the-art products

Initiate analyses and generate reports to assist with feature tracking, experiments, and product/platform health monitoring

Extract and analyze data using different data platforms (Snowflake, Python, etc.)

Present key findings to stakeholders across the company in order to drive business and product decisions

Explore new and unmapped data domains that can push our product forward

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 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

As part of the Data Infrastructure group, youll help build Lemonades data platform for our growing stack of products, customers, and microservices.

We ingest our data from our operational DBs, telematics devices, and more, working with several data types (both structured and unstructured). Our challenge is to provide building tools and infrastructure to empower other teams leveraging data-mesh concepts.

In this role youll:
Help build Lemonades data platform, designing and implementing data solutions for all application requirements in a distributed microservices environment

Build data-platform ingestion layers using streaming ETLs and Change Data Capture

Implement pipelines and scheduling infrastructures

Ensure compliance, data-quality monitoring, and data governance on data platform

Implement large-scale batch and streaming pipelines with data processing frameworks

Collaborate with other Data Engineers, Developers, BI Engineers, ML Engineers, Data Scientists, Analysts and Product managers

Share knowledge with other team members and promote engineering standards

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 Lemonades data ecosystem.

The groups mission is to build a state-of-the-art Data Platform that drives Lemonade 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 Lemonade 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 seeking our first Data Engineer to join the Revenue Operations team. This is a high-impact role where youll build the foundations of our data infrastructure connecting the dots between systems, designing and maintaining our data warehouse, and creating reliable pipelines that bring together all revenue-related data. Youll work directly with the Director of Revenue Operations and partner closely with Sales, Finance, and Customer Success.
This is a chance to shape the role from the ground up and create a scalable data backbone that powers smarter decisions across the company.
Role Overview
As the Data Engineer, you will own the design, implementation, and evolution of our data infrastructure. Youll connect core business systems (CRM, finance platforms, billing systems,) into a central warehouse, ensure data quality, and make insights accessible to leadership and revenue teams. Your success will be measured by the accuracy, reliability, and usability of the data foundation you build.
Key Responsibilities
Data Infrastructure & Warehousing
Design, build, and maintain a scalable data warehouse for revenue-related data.
Build ETL/ELT pipelines that integrate data from HubSpot, Netsuite, billing platforms, ACP, and other business tools.
Develop a clear data schema and documentation that can scale as we grow.
Cross-Functional Collaboration
Work closely with Sales, Finance, and Customer Success to understand their reporting and forecasting needs.
Translate business requirements into data models that support dashboards, forecasting, and customer health metrics.
Act as the go-to partner for data-related questions across revenue teams.
Scalability & Optimization
Continuously monitor and optimize pipeline performance and warehouse scalability.
Ensure the infrastructure can handle increased data volume and complexity as the company grows.
Establish and enforce best practices for data quality, accuracy, and security.
Evaluate and implement new tools, frameworks, or architectures that improve automation, speed, and reliability.
Build reusable data models and modular pipelines to shorten development time and reduce maintenance.

As a Data Engineer at our company, 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 our company 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 our company, 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
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Define and manage Service Level Agreements for all data sets in allocated areas of ownership
Solve challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Improve logging
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
Influence product and cross-functional teams to identify data opportunities to drive impact.