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We are looking for a motivated and business-oriented Data Engineer to join our global Data & BI team.
In this role, you will design, develop, and maintain modern data pipelines and data solutions that support critical business processes across the organization.
You will work closely with global stakeholders, integrate data from multiple sources, ensure data quality and reliability, and contribute to modern data and AI initiatives.
(*Please note, the internal title for this role is Senior Data & BI Specialist, Business Technology.)
Responsibilities:
Design, build, and maintain scalable ETL/ELT pipelines
Develop and optimize complex SQL queries and data transformation processes
Integrate data from internal and external systems, including APIs, databases, and third-party platforms
Own data quality, monitoring, reliability, and governance processes
Investigate and resolve data-related issues while supporting business users
Take ownership of data workflows from design and development through production support
Collaborate with global stakeholders to understand business requirements, analyze data discrepancies, and deliver reliable data solutions
Design, develop, and maintain AI-powered data solutions that support business decision-making and operational excellence
Build and implement monitoring capabilities (e.g. anomaly detection, forecasting, etc.) using modern AI capabilities
Partner with business teams to identify opportunities for applying AI and LLM-based solutions to real-world business challenges
Develop and operationalize AI workflows and data products from proof-of-concept through production deployment

We are hiring a senior individual contributor to join our Data Science team. This is a hands-on role for someone who can take ownership of the full solution, from understanding the problem and building the required data pipelines to developing the model, deploying it, and keeping it reliable in production. You should be comfortable working across data, code, infrastructure, and monitoring independently.
The domain is genuinely hard: noisy sensor and telemetry data, weak and delayed labels, enormous scale, and physical systems that fail in complicated ways. We use whatever technique the problem calls for, from classical machine learning and survival analysis to our own patent-pending deep learning architectures and agentic flows already running in production.
The team moves quickly and operates with a startup mentality: high ownership, short decision paths, and a strong bias toward action. When we encounter a difficult problem, we do not stop at we cant. We ask, How can we?
Moving fast does not mean cutting corners. It means combining resourcefulness and practical judgment with scientific rigor, engineering quality, and production reliability.
We also have proprietary methods for validating results against ground truth, so the feedback loop is real: when a solution works, it ships. You will see your work in production and understand its impact on real fleets.

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 & Analytics Team Lead to manage and grow our data team and own the data layer behind our AI. Youll lead a team of data analysts responsible for neural-network model analysis, model performance tracking, customer-facing and internal BI. Youll act as both the people manager and the technical lead for the team, setting technical direction while staying hands-on.
Youll thrive in this role if youre passionate about turning data into better AI products, enjoy solving complex analytical problems, and like working at the intersection of Data, Analytics, and Artificial Intelligence.
Responsibilities:
Lead the data strategy supporting AI model development, evaluation, and continuous improvement
Define KPIs and monitoring frameworks for AI model performance.
Analyze NN model outputs, build and maintain model-tracking and performance-evaluation workflows
Drive close calibration with the Algo, Product, and Data Engineering teams to align data definitions, pipelines, and metrics
Stay hands-on with SQL, Python, BI tooling, and the modern data stack
Build and own agentic data workflows - designing the context, tooling, and data access that let AI agents reliably query, analyze, and act on company data

Direct employment by the client — you'll be a company employee from day one. What if your next analysis could shape the way a B2C company grows? If you're passionate about turning complex data into meaningful business impact, this opportunity might be exactly what you're looking for. Central Israel, Hybrid: 3 days in the office | 2 days from home We're hiring a Senior Data Analyst In this role, you'll take the analytical lead on a fast-growing B2C product, partnering closely with Product, Marketing, Data Science, and Business teams to drive customer acquisition, optimize performance, and support strategic growth. What you'll be doing: • Analyze customer behavior, acquisition funnels, and marketing performance. • Lead deep-dive analyses and A/B testing initiatives. • Build dashboards and visualizations that drive business decisions. • Work with large-scale datasets and modern data platforms. • Collaborate closely with cross-functional teams to transform data into measurable business impact.

We are looking for a Senior Data Scientist to join AI team, the team behind underwriting decisions, quote-time risk scoring, and portfolio analytics.
In this role, you will own entire research directions: framing the problem, deciding what's worth measuring, designing the approach from first principles, and turning
the result into production signal. The work is production-oriented applied research on hard, real-world datasets where standard recipes don't apply and the right method
often has to be invented for the problem.
What You'll Do:
- Own open-ended research directions end-to-end - from a vague business question to a deployed, validated signal.
- Work across the team's core research areas - risk modeling, environmental and catastrophe modeling, and behavioral modeling - translating complex real-world processes
into reliable predictive signal.
- Deeply investigate existing production models - understand what they actually learn, where they break, and where the headroom is; identify and ship optimizations
grounded in that understanding.
- Design approaches from first principles when off-the-shelf methods don't fit the data.
- Build rigorous evaluations and own the result in production, not just the notebook.
- Document research clearly so findings are reproducible, auditable, and compound over time.

This is a full-time, on-site role for a Data Engineer, located in Haifa. The Data Engineer will design, build, and maintain scalable data pipelines, implement robust Extract, Transform, Load (ETL) processes, and develop efficient data models to support business intelligence and data analytics needs. The role also involves building and improving data warehousing solutions and collaborating with cross-functional teams to ensure data integrity and optimize workflows.

As a Data Engineer, you will:
Infrastructure & Pipelines
Own and maintain our data architecture end-to-end: S3, Databricks compute and administration, pipelines, logging, and our internal tooling
Keep the platform healthy and reliable - the data we serve feeds product decisions and customer-facing AI, so correctness and uptime matter
Integrate new data sources and maintain existing ones, handling the messy realities (format changes, awkward upstream systems like NetSuite, schema drift)
Performance & Cost
Identify bottlenecks and optimize for both compute and cost - parallelize workloads, tune table and cluster settings, and keep our Databricks spend sane as we scale. We use AI coding tools heavily to move fast here, but the engineering judgment is yours
Data Access & Reliability
Build and maintain the semantic layer that exposes our data reliably and consistently to analysts and AI tools, so the same question always returns the same trustworthy answer
Implement PII handling and row- and column-level security so sensitive data stays protected everywhere it's consumed.

We're hiring a Director of Data to lead our company's data function and build our data into a
real competitive moat. You'll report to the CPO, manage and grow our lean data team, and
partner across the leadership table. The role is roughly 70% Build & Operate, 30% Lead &
Influence in year one, shifting toward 50/50 as the team scales.
About us
we are an insurance marketplace and aggregator. We connect thousands of
independent insurance agencies with a wide network of carriers, MGAs, and wholesalers. We
sit at a vantage point neither agents nor carriers have on their own, and turning that asymmetric
view into proprietary intelligence is one of the most important things we'll do over the next
several years.
What you'll do
Lead and grow our data team. Set direction, raise the bar, make their job better.
Make self-service analytics real across our company, so every leader gets to their
answers without queuing behind the data team.
Create a contracts-based partnership with the engineering teams producing source data.
Build a core proprietary data asset that powers our internal and partner-facing
experiences and anchors real conversations with our carriers.
Own the data infrastructure roadmap and the question of how we evolve our data
engineering investment over the next 12-24 months.
Define how AI gets leveraged across our data stack and analytical workflows.
Be the data partner the leadership team actually wants to call.

Required Senior Data Engineer
Full-time
Company Description:
A dynamic technology firm dedicated to building exceptional products using modern technologies for the world's most admired companies. We pride ourselves on innovation, collaboration, and delivering excellence in every project.
Responsibilities:
Design and maintain scalable data pipelines with Spark Structured Streaming.
Implement Lakehouse architecture with Apache Iceberg.
Develop ETL processes for data transformation.
Ensure data integrity, quality, and governance.
Collaborate with stakeholders and IT teams for seamless solution integration.
Optimize data processing workflows and performance.
Additional Information:
Location: Ra'anana

We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
Key Responsibilities:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

At our company, data isn't just for dashboards - it's the nervous system of our future products. As we expand into smart lighting (Oasis) and living tech (Easyplant), we need to process massive streams of IoT signals and power real-time AI. You won't just maintain a warehouse; you will architect the platform that connects our physical products to the digital world.
What youll do
Build the "Brain": Architect the next-gen data platform capable of handling high-volume IoT streams and integrating AI capabilities into our daily operations.
Code the Core: This is a hands-on role. You wont just manage; youll be deep in Python, DBT, and Airflow, building and optimizing the pipelines yourself.
Scale for Complexity: We are growing from one product to a multi-brand ecosystem. You will ensure our data infrastructure evolves to support diverse business lines without becoming a bottleneck.
Democratize Insights: Build a system so robust and intuitive that every engineer, product manager, and marketer can self-serve the data they need to build better products.

As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.

If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!

Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.