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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 our 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 are looking for a brilliant Data Engineer- an independent, logical thinker who enjoys solving complex problems and building scalable data solutions. You will own and evolve the data foundations that power Product, Finance, Operations, and Business teams. Working closely with diverse stakeholders, Analysts, and R&D teams, you will serve as a technical partner, translating complex business challenges into robust data models, pipelines, and infrastructure. You should be able to translate business and data requirements into scalable data pipelines and data models, integrating multiple internal and external data sources using the most appropriate technologies. Beyond building pipelines, you will improve data quality, modernize existing data assets, automate manual workflows, and help create a clean, reliable, and scalable data ecosystem that supports the company's growth.
Roles and Responsibilities:
Design and build end-to-end data pipelines - From defining source structures and integrating APIs to delivering clean, trusted datasets that enable analytics, reporting, and operational workflows.
Translate business needs into scalable data solutions based on business priorities and the product roadmap, understand technical requirements, and deliver purpose-built pipelines and tools.
Act as the technical partner for Product, Finance, Operations, and R&D teams, translating business needs into scalable data models, pipelines, and internal tools while ensuring reliable, trusted data across the organization.
Write high-quality, maintainable code, while following best practices and leveraging modern data tooling and CI/CD principles.
Drive data quality and reliability - Monitor, validate, troubleshoot, and continuously improve data quality and pipeline reliability across the data platform.

Were looking for a data-driven and business-savvy Analyst to join our growing data team.
In this role, youll work closely with our Marketing, Finance, and Sales teams to analyze performance, connect marketing and financial data, and build models that support strategic decisions.
Youll play a key role in translating data into clear business insights that drive growth, efficiency, and profitability.
Key Responsibilities:
Partner with Marketing, Finance, and Sales teams to analyze performance, efficiency, and ROI.
Evaluate UA spend, ROAS, and growth metrics across channels, campaigns, and regions.
Build and maintain dashboards and reports in Cursor, Tableau and Looker to track key business and financial KPIs.
Develop and maintain risk models that help guide company decisions and improve forecasting accuracy.
Conduct cohort and funnel analysis to identify performance trends and growth opportunities.
Collaborate with Data engineering and finance teams to align top level metrics with company financial reporting.
Present actionable insights and recommendations that influence both strategy and operations.

Were looking for experienced, hands-on researchers who have repeatedly taken complex AI capabilities from initial problem definition to real-world use. Expect scarce data, noisy labels, and problems without an established playbook. Youll have the autonomy to shape the approach-and the responsibility to make it work.
Responsibilities
Our Research Tracks:
Were hiring across four tracks. We expect deep expertise in at least one, not mastery of all four.
Agents: Self-improving agents, learning from execution traces, and user feedback. Genetic and evolutionary optimization of workflows, tools, and code
NLP: Reinforcement learning for language models, distillation, retrieval and embeddings, named-entity and relation extraction, and multilingual learning.
Vision & Audio: Visual and speech understanding, detection and segmentation, multimodal representation learning, grounding, and cross-modal retrieval.
Machine Learning: Representation and graph learning, probabilistic and causal modeling, optimization, and learning with limited or noisy data.
What Youll Own:
Take research from an open-ended problem to a working capability: define success, develop the data and methods, run rigorous experiments to make it work. Work closely with engineering through deployment, measuring quality, efficiency, not just benchmark scores. Drive progress through technical blockers, adapt when an approach fails, and strengthen the team through collaboration, technical review, and mentoring.

We are looking for an experienced and highly motivated Senior FinOps Product & Projects Analyst to join our Financial Operations (FinOps) organization.
This role sits within the FinOps Product & Projects team, which acts as the bridge between Financial Operations, Product, Engineering, BI, and other cross functional teams.
Our mission is to ensure that FinOps is operationally ready to support new products, capabilities, and strategic initiatives. We translate business and operational needs into product requirements, design scalable operational processes, drive cross functional projects, and ensure successful implementation across the FinOps organization.
This is a highly cross functional role combining project management, product operations, process design, data analysis, and technical problem solving.
What You'll Do :
Lead strategic FinOps initiatives from planning through execution.
Drive cross functional projects involving Product, Engineering, BI, Finance, Operations, and external stakeholders.
Track project progress, identify risks, and drive timely resolution of blockers.
Coordinate testing, deployment readiness, and operational rollout of new capabilities.
Act as the primary liaison between FinOps and Product teams.
Translate operational challenges into clear product requirements and enhancement proposals.
Identify opportunities for automation, scalability, and operational efficiency.
Ensure new product capabilities are operationally supported before launch.
Influence product roadmaps based on operational needs and customer impact.
Design scalable operational processes for new products and business initiatives.
Build and document standard operating procedures (SOPs), workflows, and operational playbooks.
Ensure smooth handover of newly designed processes to operational FinOps teams.
Lead complex operational investigations involving multiple teams.
Coordinate high priority incident resolution.
Perform root cause analysis and drive long term corrective actions.
Work closely with BI teams to define reporting requirements and operational dashboards.
Support data driven decision making across FinOps.

Required Senior Data Engineer
Description
We are making the future of Mobility come to life starting today.
We support the worlds largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.
At the heart of our platform lies the data infrastructure, driving advanced machine learning models and optimization algorithms. As the owner of data pipelines, you'll tackle diverse challenges spanning optimization, prediction, modeling, inference, transportation, and mapping.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platform-supporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do:
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.

we are looking for a hands-on Data Platform Engineer to operate and evolve our enterprise Kafka ecosystem, which serves as the companys central data streaming platform. The role is critical to our data infrastructure and supports a major ongoing migration to the cloud, while covering production operations, troubleshooting, automation, maintenance, and reliability across high-volume, low-latency, 24/7 on-premises and cloud environments.
Responsibilities:
Operate and monitor Kafka environments across Confluent Cloud, Confluent Platform, and Kubernetes/CFK deployments, including availability, consumer lag, replication, throughput, latency, storage, and capacity.
Troubleshoot production incidents, participate in on-call, perform root-cause analysis, and improve resilience, failover, and disaster-recovery readiness.
Manage topics, partitions, retention, ACLs, consumer groups, Kafka Connect connectors, and Schema Registry.
Deploy, configure, upgrade, patch, and scale platform components and connectors while maintaining secure access and configuration consistency.
Automate platform operations and provisioning using scripting, infrastructure-as-code, and CI/CD.
Work with DevOps, SRE, Infrastructure, Security, Architecture, Data, and application teams to onboard workloads and continuously improve platform reliability and governance.

We are Tailor Brands. We built a platform that builds businesses. FromWere Looking for a Product Analyst - Join Our data Driven Journey! As a data -driven organization, insights from our data Team are essential to shape our strategy and improve the experiences of our customers. Were looking for a highly motivated data analyst to join our team and work in a dynamic Big Data environment You are detail-oriented, analytical, and passionate about understanding user behavior. In this role, youll turn data into actionable insights, influence product decisions, and help drive the success of our platform.
Key Responsibilities Analyze user behavior: Monitor and evaluate website activity patterns and user flows to enhance usability and Customer Experience. AB Testing: Conduct in-depth analysis of AB tests to provide stakeholders with actionable, data -driven recommendations for product and user value enhancements. Metric Monitoring & Insights: Track product performance metrics, identify trends, and raise alerts on significant changes. Perform periodic and ad-hoc analyses to recommend impactful solutions. Visualization & Reporting: Create and maintain dashboards, reports, and daily summaries that present key SaaS metrics and actionable insights. Collaborate Cross-Functionally: Work closely with teams across Product, Marketing, Customer Success, Finance, and Management to support data -driven decision-making.

we are looking for a Manager, Data Science & Research.
What will you do:
Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps
Design and build models across computer vision, NLP, and multimodal pipelines
Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment
Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)
Improve model quality (precision/recall) while balancing cost, latency, and scale
Drive automation systems (auto-labeling, auto-curation, retraining loops)
Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems
Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward
Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

Were looking for a BI & Data Engineering Team Lead to join our BI team and take end-to-end ownership of high-impact analytics foundations while mentoring a team of 4-6 talented BI Data Engineers. 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.
In this role, you'll combine people leadership with hands-on technical depth (roughly 30% of your time), owning the roadmap, architecture, and delivery of BI platform. Youll shape how AI and agentic workflows transform the way BI is built and consumed, helping raise the bar for analytics engineering across the company.
Hands-on experience using GenAI to improve analytics engineering 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.

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.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

We're looking for a Senior Data Platform Engineer to join the Data Platform team, which owns the infrastructure every data team at Lusha runs on and sits between DevOps and the Data groups. You'll be the Databricks admin (Unity Catalog, compute, governance, cost), the Confluent (Kafka) and CDC admin, and own Airflow, Elasticsearch, the databases, the data S3 estate, and the Kubernetes cluster underneath. Your job is to make the platform fast, cheap, governed, and boring: if it's broken, you fix it, if it's manual, you automate it.
Hands-on experience using AI coding tools daily, and building or integrating LLM and agent tooling into real workflows, 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.

Required Principal/ Senior Data Scientist - LLM Agents
Job Summary
As a Data Scientist, you will apply your expertise in software engineering, LLM agents, and cybersecurity to build new defense techniques against cyber-villains. You will be a driving force in designing and developing groundbreaking, Agentic LLM-based security solutions that block attacks before they begin. Join our innovative team to shape the future of cybersecurity and impact millions of customers.
Important: this role requires a unique combination of hands-on software engineering skills as well as previous experience with designing and delivering LLM-driven products.
Key Responsibilities:
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach.
Design and implement agentic LLM solutions to face modern cybersecurity challenges.
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders.
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.

Required Principal Data Engineer (Cortex)
Job Summary
As a Principal Data Engineer, you will be integral to the security research group, designing, building, and maintaining the data pipelines and data frameworks that are the backbone of our cyber attack detection capabilities. You will work closely with top security and AI researchers, enabling their work and seeing the direct impact of your contributions on our services and the day-to-day effectiveness of the research team.
Key Responsibilities:
Lead the design and implementation of end-to-end, complex data pipelines and data platforms in cloud environment.
Collect, analyze, and translate complex data requirements from various stakeholders including data analysts, developers, and Cyber security researchers.
Develop robust, scalable Cloud based data solutions using Python and distributed processing frameworks such as Apache Beam (Dataflow) , GKE , Spark , etc.
Utilize AI as part of the development cycle, including generating, reviewing, and testing code via prompts.
Model and manage data within cloud MPP databases and data lakes such as BigQuery, Redshift, or Snowflake.