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Required Research Infra Engineer
The Dream Job
As a Research Infra Engineer, you will build and operate the shared platforms that power our cyber research: data ingestion, connectivity to internal/external systems, scalable analysis environments, and self-serve tools which allow the team moving faster.
Youll partner closely with CyberAI researchers to translate research needs into reliable, secure, cloud-deployed capabilities used across the group. Your goals are to reduces research-toil, improves reproducibility and code quality, and accelerates the path from prototype to shared capability.
Responsibilities
Design, implement, and iterate on internal platforms that support research workflows (e.g., data ingestion, enrichment, indexing, search, labeling, evaluation harnesses, experiment tooling).
Develop durable pipelines and connectors to bring in and normalize research data sources.
Create reusable libraries, templates, CLIs, and services that enable researchers to run analyses and experiments safely and repeatably.
Own deployments, reliability, observability, access control, and cost/performance of the research stack so its usable by all researchers.
Work closely with CyberAI researchers on the development of next-generation artificial cyber researchers and AI-driven analysis capabilities.

We are looking for a Data Engineer to join our usage metering & billing platform team! with a strong background in writing ETLs and complicated data processing pipelines. Youre deeply familiar with modern data processing stack (especially Spark, Hadoop and Airflow), have a strong problem-solving attitude and, most importantly, youre passionate about understanding the business side of the platform. Our platform engineers have an end-to-end understanding of the data our products generate and the commercial models and data structures in which they fit.
Working with this enormous volume of data begins with massive ETL pipelines built using cutting-edge technologies such as Kafka, BigQuery, Airflow, S3, PostgreSQL, Athena, SQS, Redis, and especially Spark. We are big believers in working with the right tool for the right job, including programming languages. We run a truly polyglot shot with Scala, Python, Go and Node being especially common here . The extreme growth rate of our data and client base means that solutions need to be designed to handle 10X growth or more.
What youll do:
Develop end-to-end ETLs and data infrastructure features from data processing logic to database choice and implementation through to API development
Improve the scalability and performance of existing data pipelines
Delve into existing pipelines and business logic, target weaknesses and add functionality
Mentor, advise, and work collaboratively within the Biz Data & Dev group, with other development teams, and with all other business teams of the company
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible

We are looking for a Data Engineer to join our usage metering & billing platform team! with a strong background in writing ETLs and complicated data processing pipelines. Youre deeply familiar with modern data processing stack (especially Spark, Hadoop and Airflow), have a strong problem-solving attitude and, most importantly, youre passionate about understanding the business side of the platform. Our platform engineers have an end-to-end understanding of the data our products generate and the commercial models and data structures in which they fit.
Working with this enormous volume of data begins with massive ETL pipelines built using cutting-edge technologies such as Kafka, BigQuery, Airflow, S3, PostgreSQL, Athena, SQS, Redis, and especially Spark. We are big believers in working with the right tool for the right job, including programming languages. We run a truly polyglot shot with Scala, Python, Go and Node being especially common here . The extreme growth rate of our data and client base means that solutions need to be designed to handle 10X growth or more.
What youll do:
Develop end-to-end ETLs and data infrastructure features from data processing logic to database choice and implementation through to API development
Improve the scalability and performance of existing data pipelines
Delve into existing pipelines and business logic, target weaknesses and add functionality
Mentor, advise, and work collaboratively within the Biz Data & Dev group, with other development teams, and with all other business teams of the company
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible

We're looking for a Product Manager to own all of data export products end-to-end. This is a hands-on role with high customer exposure: you'll work directly with enterprise clients to understand their data access needs, partner closely with internal stakeholders across the organization, and ship improvements across multiple product surfaces in parallel. If you thrive on juggling priorities, communicating clearly across audiences, and turning customer feedback into shipped products, this role is for you.
What you'll do:
Own all of data export products throughout their lifecycles, from discovery and definition through delivery, adoption, and iteration
Partner directly with enterprise customers and internal stakeholders to understand data export pain points and translate them into clear requirements
Prioritize effectively across multiple product surfaces and competing stakeholder needs
Drive cross-functional alignment with engineering and business teams to deliver high-quality features on time
Define and communicate product roadmap, trade-offs, and decisions clearly, both to internal teams and customer-facing audiences
Continuously improve usability, reliability, and documentation based on customer feedback and usage data
Strengthen and expand data export products as the foundation for customers' AI and advanced analytics initiatives by ensuring we deliver the right data, in the right format, at the right cadence

Were looking for a Senior Data & Analytics Architect to join our team and work directly with startup CTOs, engineering teams, and account teams. This is a hands-on, customer-facing architecture role where you will design and deliver production-grade data platforms on AWS.
The role is focused on turning real business problems into working systems, from early discovery and architecture design to supporting implementation. This is not a pure strategy or management role, its about making clear technical decisions and ensuring they hold up in production.
📍 Work location: hybrid from Tel Aviv
Key Responsibilities
Design and deliver end-to-end data platforms on AWS, covering ingestion, storage, processing, and serving layers, including Well-Architected reviews and contribution to SOWs and HLDs
Work directly with startup customers to understand requirements, challenge assumptions, and shape practical solutions
Lead technical discussions, workshops, architecture reviews, and POCs
Translate ideas and early concepts into clear architectures, including HLDs, SOWs, and implementation direction
Make and explain trade-offs across cost, performance, scalability, and complexity
Stay close to delivery, supporting teams to ensure solutions are implemented correctly
Collaborate with Data Engineers, DevOps, Solution Architects and Account Managers to move projects from concept to production
Contribute to internal standards, reusable patterns, and reference architectures
Operate in a fast-paced, project-based environment with multiple customer engagements
Stay up to date with modern Data Engineering and Analytics practices, and contribute to internal enablement, patterns, and knowledge sharing
Work in a customer-facing environment that includes occasional travel, both locally for meetings and events, and internationally around once per quarter

We're looking for a Senior Data Engineer to design, build, and scale the streaming services at the heart of our next-generation data platform. This is an individual contributor role for an engineer who has spent years in Kafka and Java, who knows what it takes to keep microservices healthy under real load, and who treats GenAI as part of the toolkit rather than a buzzword.
This job is located in Tel Aviv (hybrid).
About Us
At our company, were creating the industrys leading SASE platform, merging advanced security with seamless connectivity. Our mission is to empower businesses to thrive in a cloud-first world, and data is at the heart of this transformation.
Why Youll Love This Role
Design and scale real-time data pipelines that process tens of millions of events per hour, end to end
Work with cutting-edge technologies - Kafka, Java microservices, AWS, and modern GenAI tooling across the SDLC
Set technical direction for a domain that directly affects customers globally
Key Responsibilities
Architect, build, and own scalable Java microservices for streaming ingestion, enrichment, and processing
Drive Kafka design decisions - topics, partitioning, consumer groups, back-pressure, delivery semantics and tune them for throughput and reliability
Make scaling calls based on data: load tests, profiling, capacity planning, and production telemetry
Embed GenAI across the SDLC : code generation, code review, test authoring, debugging, design exploration and share your knowledge with the team
Partner with architects, product managers, and data consumers to turn ambiguous requirements into resilient systems.

We are seeking a skilled Senior / Data Engineer to lead end-to-end data solutions, from mapping business needs through development and implementation. This role requires a strong technical background to design, build, and maintain data pipelines and automation processes that support data-driven decision-making within the Clinical Research department. The position combines hands-on data engineering, analytics, and dashboard development, with a focus on building reliable data infrastructure and enabling AI-driven initiatives.
The Senior / Data Engineer - Automation, Analytics & AI (AA & AI) operates at the country level within GCTO RRO to identify, design, and deliver technology-enabled solutions that improve clinical trial operations efficiency, quality, and compliance. The role leads the intake, assessment, and delivery of local automation, analytics, and AI initiatives, creates compelling business cases, builds or oversees development of country tools, and scales fit-for-purpose solutions to other countries or the Region when applicable.
The Senior / Data Engineer - Automation, Analytics & AI (AA & AI) reports to the Clinical Operations Manager Lead (COM Lead) and partners closely with country, regional and headquarters roles and teams, such as, Regions Operational Excellence (ROE), regional/country stakeholders, Automation/Analytics/AI partners and, as needed, IT. As needed, the Sr BA may also support initiatives driven by Regional Operations teams, such as GSA, GTO, GSBP and EDM. The role ensures adherence to ICH GCP, company policies, and local regulations, and drives measurable impact through robust KPIs and change enablement.

You are a Software Data Engineer with deep experience building data-intensive systems, not a traditional ETL or BI-focused Data Engineer. In this role, you will design and build production-grade data services, platforms, and pipelines that power DIH and our AI-driven products. You will combine strong software engineering fundamentals with modern data engineering practices, with a focus on clean architecture, reliability, scalability, observability, and testing.

As a Software Data Engineer, Data Platform, you will:
Build and evolve Python-based services and pipelines that ingest raw industrial events, store them reliably, and expose clean, well-modeled tables and APIs for downstream consumers, including Digital Twin, Smart Canvas, AI agents, and analytics.
Design systems that handle duplicates, invalid data, late-arriving events, and reprocessing in a principled, incremental, and reproducible manner.
Collaborate with platform, machine learning, and product teams across Israel and globally to transform complex data challenges into robust, observable, and scalable software solutions.

Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. 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.
We believe three things matter for every role at Lemonade: 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.

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across .
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build next-generation data stack.
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 you'll
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals

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

we are seeking a Senior Data Infra Engineer. You will be responsible for designing and building all data, ML pipelines, data tools, and cloud infrastructure required to transform massive, fragmented data into a format that supports processes and standards. Your work directly empowers business stakeholders to gain comprehensive visibility, automate key processes, and drive strategic impact across the company.

Responsibilities

Design and Build Data Infrastructure: Design, plan, and build all aspects of the platform's data, ML pipelines, and supporting infrastructure.
Optimize Cloud Data Lake: Build and optimize an AWS-based Data Lake using cloud architecture best practices for partitioning, metadata management, and security to support enterprise-scale operations.
Lead Project Delivery: Lead end-to-end data projects from initial infrastructure design through to production monitoring and optimization.
Solve Integration Challenges: Implement optimal ETL/ELT patterns and query techniques to solve challenging data integration problems sourced from structured and unstructured data.

we are seeking a Senior Software Engineer (Data Engineering). You will be responsible for designing and building all data, ML pipelines, data tools, and cloud infrastructure required to transform massive, fragmented data into a format that supports processes and standards. Your work directly empowers business stakeholders to gain comprehensive visibility, automate key processes, and drive strategic impact across the company.

Responsibilities

Design and Build Data Infrastructure: Design, plan, and build all aspects of the platform's data, ML pipelines, and supporting infrastructure.
Optimize Cloud Data Lake: Build and optimize an AWS-based Data Lake using cloud architecture best practices for partitioning, metadata management, and security to support enterprise-scale operations.
Lead Project Delivery: Lead end-to-end data projects from initial infrastructure design through to production monitoring and optimization.
Solve Integration Challenges: Implement optimal ETL/ELT patterns and query techniques to solve challenging data integration problems sourced from structured and unstructured data.

Were looking for a Data Engineer to join our company. This is a hands-on, cross-functional role focused on owning and improving our data quality, pipeline reliability, and modeling infrastructure. Youll be responsible for managing and optimizing our DBT models, ETL processes, and data connectors - and will work closely with product, operations, and engineering teams to ensure data is accurate, consistent, and accessible.

You should be someone who thrives on autonomy, takes pride in clean and scalable solutions, and enjoys helping others get the data they need.

In this role you will
Architect our entire DBT project and data warehouse structure completely from scratch-a rare, high-impact opportunity
Lead data modeling efforts: Translating business needs into scalable, reliable data models
Build and monitor data pipelines and connectors from various internal and external systems
Ensure high standards of data quality, consistency, and documentation
Collaborate with engineering, product, and operations teams to understand needs and build data solutions
Proactively detect data issues and work to resolve them
Help define and improve internal data best practices and standards
Support data governance efforts and advocate for trustworthy, well-modeled data
You will be one of the pioneers of a new team - passion & energy is required