דרושים » דאטה » Director of Data & Analytics

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 our data ecosystem.

The groups mission is to build a state-of-the-art Data Platform that drives us 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 us 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.

Required Analytics Engineer
Tel Aviv
Want to shape how data drives product decisions?
As an Analytics Engineer, youll design the foundations of our data infrastructure, build robust and scalable data models, and empower teams across the organization with actionable insights that fuel our product direction.
As an Analytics Engineer, you will:
Design and implement robust data models to transform raw data into analytics-ready tables, enabling confident decision-making across product and business teams.
Own and maintain our dbt pipelines with a focus on scalability, modularity, and clear documentation.
Continuously evolve our data models to reflect changing business logic and product needs.
Build and maintain comprehensive testing infrastructure to ensure data accuracy and trust.
Monitor the health of our data pipelines, ensuring integrity in event streams and leading resolution of data issues.
Collaborate closely with analysts, data engineers, and product managers to align data architecture with business goals.
Guide the analytics code development process using Git and engineering best practices.
Create dashboards and reports in Tableau that turn insights into action.
Drive performance and cost optimization across our data stack, proactively improving scalability and reliability.

we are looking for a Data Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance.

we are a fast-growing digital health SaaS company thats on a mission to transform the way physicians interact with patient data. Thousands of clinicians across the United States already use our companys AI-powered solution that transforms complex and fragmented patient data into concise patient portraits" and actionable clinical insights at the point of care. With our company, physicians experience less burnout, reduce missed diagnoses, and can devote more time to giving better care to their patients.
our company has been named one of the Top 100 AI companies globally by CB Insights and made the list of the Top 50 Digital Health startups. We are already working with industry-leading value-based organizations including Privia Health and Agilon.
We're currently seeking a Senior Data Researcher to join our Data Team and help proactively guide our business growth through the provision of strategic perspective, market insight, and experience with analytical tools and techniques. You will work closely with product managers, medical analysts, and the engineering team and bring your expert analytical ability to provide key insights, recognize key opportunities, and drive strategic initiatives forward.
Responsibilities
Work with product, medical, and engineering teams to turn data into insights and recommendations.
Conduct exploratory analysis to identify opportunities for new features, model their impact, and drive performance improvements.
Build and maintain dashboards to improve data visibility and monitoring.
Analyze product performance, user behavior, and interactions to showcase product value.
Define, measure, and build monitoring tools for key KPIs.
Visualize insights clearly to improve understanding and decision-making.
Support roadmap planning by identifying trends, gaps, and opportunities.

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.

We are looking for a Senior Data Analyst to join our companys Professional Services group. As a data-driven organization, we strive for absolute transparency around our deliverables, empowering relevant teams to make informed decisions and become more productive and efficient.
How youll make an impact:
Analyze, discover, monitor and provide insights on major revenue impact issues to ensure our company Network performance and high quality.
Create, support and maintain development tools aiming to monitor and investigate our company performance, as well as find creative solutions for a variety of challenges, while facing our growing data requirements
Own and manage multiple data initiatives and projects both on an on-going and an ad-hoc basis, while using new approaches of data analytics
Analyze business data, discover root causes for data anomalies and generate actionable recommendations
Closely work with multi-disciplinary teams and stakeholders to provide insights and answer business questions.

We are looking for a Senior Data Engineer to join our Platform group in the Data Infrastructure team.
Youll work hands-on to design and deliver data pipelines, distributed storage, and streaming services that keep our companys data platform performant and reliable. As a senior individual contributor you will lead complex projects within the team, raise the bar on engineering best-practices, and mentor mid-level engineers while collaborating closely with product, DevOps and analytics stakeholders.
Code & ship production-grade services, pipelines and data models that meet performance, reliability and security goals
Lead design and delivery of team-level projects from RFC through rollout and operational hand-off
Improve system observability, testing and incident response processes for the data stack
Partner with Staff Engineers and Tech Leads on architecture reviews and platform-wide standards
Mentor junior and mid-level engineers, fostering a culture of quality, ownership and continuous improvement
Stay current with evolving data-engineering tools and bring pragmatic innovations into the team.

We are looking for a hands-on data infrastructure and platform engineer with proven leadership skills to lead and evolve our self-service data platform that powers petabyte-scale batch and streaming, near-real-time analytics, experimentation, and the feature platform. Youll guide an already excellent team of senior engineers, own reliability and cost efficiency, and be the focal point for pivotal, company-wide data initiatives- feature platform, lakehouse, and streaming.
Own the lakehouse backbone: Mature Iceberg at high scalepartitioning, compaction, retention, metadataand extend our IcebergManager in-house product to automate the lakehouse management in a self serve fashion.
Unify online/offline for features: Drive Flink adoption and patterns that keep features consistent and low-latency for experimentation and production.
Make self-serve real: Build golden paths, templates, and guardrails so product/analytics/DS engineers can move fast safely.
Run multi-tenant compute efficiently: EMR on EKS powered by Karpenter on Spot instances; right-size Trino/Spark/Druid for performance and cost.
Cross-cloud interoperability: BigQuery + BigLake/Iceberg interop where it makes sense (analytics, experimentation, partnership).
What you'll be doing
Leading a senior Data Platform team: setting clear objectives, unblocking execution, and raising the engineering bar.
Owning SLOs, on-call, incident response, and postmortems for core data services.
Designing and operating EMR on EKS capacity profiles, autoscaling policies, and multi-tenant isolation.
Tuning Trino (memory/spill, CBO, catalogs), Spark/Structured Streaming jobs, and Druid ingestion/compaction for sub-second analytics.
Extending Flink patterns for the feature platform (state backends, checkpointing, watermarks, backfills).
Driving FinOps work: CUR-based attribution, S3 Inventory-driven retention/compaction, Reservations/Savings Plans strategy, OpenCost visibility.
Partnering with product engineering, analytics, and data science & ML engineers on roadmap, schema evolution, and data product SLAs.
Leveling up observability (Prometheus/VictoriaMetrics/Grafana), data quality checks, and platform self-service tooling.

Were looking for a Product Analyst to join our Product team and play a critical role in unlocking the power of maritime data. Youll dive deep into complex datasets, ensuring quality, uncovering insights, and shaping the foundation for products and workflows built on AI. Your work will directly contribute to product innovation, customer impact, and the next generation of AI-driven maritime solutions.

What will you do?

Extract, analyze, and interpret maritime data using Python, SQL, and other data tools, working across sources such as Rockset, MongoDB, and S3.
Ensure data quality, accuracy, and consistency, supporting both product development and Generative AI-powered workflows.
Identify patterns, anomalies, and emerging risks within large, complex datasets to drive actionable insights for customers and internal stakeholders.
Collaborate with product managers, engineers, and data scientists to optimize data pipelines, workflows, and models.
Support the development of strategies for handling structured and unstructured data, contributing to scalable, automated solutions.
Visualize and communicate findings effectively, using tools such as Matplotlib, Grafana, or Redash, tailored for technical and non-technical audiences.
Apply domain knowledge of the maritime industry to contextualize data and generate meaningful insights for product workflows.
Conduct data integrity and QA checks, ensuring reliability for both operational use and AI model training.

we are a fast-growing digital health SaaS company thats on a mission to transform the way physicians interact with patient data. Thousands of clinicians across the United States already use our companys AI-powered solution that transforms complex and fragmented patient data into concise patient portraits" and actionable clinical insights at the point of care. With our company , physicians experience less burnout, reduce missed diagnoses, and can devote more time giving better care to their patients.
our company has been named one of the Top 100 AI companies globally by CB Insights and made the list of the Top 50 Digital Health startups. We are already working with industry-leading value-based organizations including Privia Health and Agilon.
we are looking for a talented and experienced Data Engineer to join our data group.
The team is responsible for processing and transforming data from multiple external sources while building and maintaining an internal serving platform. Our key challenges include operating at scale, integrating with diverse external interfaces, and ensuring the data is served in a consistent and reliable manner.
Responsibilities
Designing and implementing our companys data platform
Transforming, modeling, and serving all our companys medical data.
Utilize data best practices, to improve the product and allow data-driven decision-making.
Collaborate closely with cross-functional teams to understand business requirements and translate them into data-driven solutions.
Stay updated with the latest research and advancements in the data field.