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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 companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company 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 our company 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.

As a Data Engineer Tech Lead, you will play a central role in shaping our data strategy and guiding the team in building and optimizing analytics data pipelines that power business decisions across the organization. Beyond driving complex data initiatives, youll be a hands-on mentor and technical advisor, supporting other data engineers, fostering a culture of collaboration, and ensuring the teams overall growth and success.
Key Responsibilities:
Lead and mentor a team of data engineers, providing technical guidance, support, and regular feedback to enable their growth.
Architect, design, and evolve robust, scalable data pipelines and ETL/ELT processes for diverse structured and unstructured data sources.
Serve as a technical advisor for data best practices across the organization, collaborating with data analysts, data scientists, engineers, and product managers.
Define and evolve analytics-focused data models that empower business stakeholders with timely and reliable data.
Drive initiatives to improve data quality, governance, and observability across the analytics stack.
Act as a bridge between technical and non-technical stakeholders, helping translate business needs into actionable data solutions.
Champion engineering excellence, including code reviews, documentation, and knowledge-sharing.
What your day might look like:
Leading the most complicated data projects our company has to offer Hands on
Supporting other engineers by reviewing code, troubleshooting architecture, and encouraging best practices.
Leading the technical direction of new pipelines or data modeling initiatives.
Meeting with product managers and analysts to align on priorities and define the right data solutions.
Guiding your team through design discussions, trade-offs, and implementation decisions.
Helping the team deliver with high reliability, scalability, and speed.
Driving initiatives that improve the maintainability, observability, and impact of the data platform.

Were looking for a Data Engineer for the Insight Team to join our Data Group and a new team responsible for developing innovative features based on multiple layers of data. These features will power recommendation systems, insights, and more. This role involves close collaboration with the core teams within the Data Group, working on diverse data pipelines that tackle challenges related to scale and algorithmic optimization, all aimed at enhancing the data experience for our customers.
Where does this role fit in our vision?
Every role at our company is designed with a clear purposeto integrate collective efforts into our shared success, functioning as pieces of a collective brain. Data is everything, its at the heart of everything we do. The Data Group is responsible for shaping the experience of hundreds of thousands of users who rely on our data daily.
The Insight Team monitors user behavior across our products, leveraging millions of signals and time-series entities to power a personalized recommendation and ranking system. This enables users to access more unique and tailored data, optimizing their experience while maintaining a strong focus on the key KPIs that drive the success of our Data Group.
What will you be responsible for?
Develop and implement robust, scalable data pipelines and integration solutions within our Databricks-based environment.
Develop models and implement algorithms, with a strong emphasis on delivering high-quality results.
Leverage technologies like Spark, Kafka, and Airflow to tackle complex data challenges and enhance business operations.
Design innovative data solutions that support millions of data points, ensuring high performance and reliability.

Required Senior Data Engineer
What You'll Do:
Shape the Future of Data- Join our mission to build the foundational pipelines and tools that power measurement, insights, and decision-making across our product, analytics, and leadership teams.
Develop the Platform Infrastructure - Build the core infrastructure that powers our data ecosystem including the Kafka events-system, DDL management with Terraform, internal data APIs on top of Databricks, and custom admin tools (e.g. Django-based interfaces).
Build Real-time Analytical Applications - Develop internal web applications to provide real-time visibility into platform behavior, operational metrics, and business KPIs integrating data engineering with user-facing insights.
Solve Meaningful Problems with the Right Tools - Tackle complex data challenges using modern technologies such as Spark, Kafka, Databricks, AWS, Airflow, and Python. Think creatively to make the hard things simple.
Own It End-to-End - Design, build, and scale our high-quality data platform by developing reliable and efficient data pipelines. Take ownership from concept to production and long-term maintenance.
Collaborate Cross-Functionally - Partner closely with backend engineers, data analysts, and data scientists to drive initiatives from both a platform and business perspective. Help translate ideas into robust data solutions.
Optimize for Analytics and Action - Design and deliver datasets in the right shape, location, and format to maximize usability and impact - whether thats through lakehouse tables, real-time streams, or analytics-optimized storage.
You will report to the Data Engineering Team Lead and help shape a culture of technical excellence, ownership, and impact.

Were looking for a Data Engineer to design and implement high-scale, data-intensive platforms, research and develop algorithmic solutions, and collaborate on key company initiatives. You will play a critical role within our core data teams, which are responsible for managing and optimizing our fundamental data assets.
Where does this role fit in our vision?
Every role at our company is designed with a clear purposeto integrate collective efforts into our shared success, functioning as pieces of a collective brain. Data is at the heart of everything we do. Our data engineers are responsible for building and maintaining the core products that power our business. The data teams own and manage the pipelines that generate our assets, with a strong focus on optimizing key company KPIs.
We leverage cutting-edge technologies to build and scale our data infrastructure. In this role, you will work closely with Data Scientists and Data Analysts on a daily basis, collaborating to develop innovative data solutions that drive business impact.
What will you be responsible for?
Solve Complex Business Problems with Scalable Data Solutions
Develop and implement robust, high-scale data pipelines to power our core assets.
Leverage cutting-edge technologies to tackle complex data challenges and enhance business operations.
Collaborate with Business Stakeholders to Drive Impact
Work closely with Product, Data Science, and Analytics teams to define priorities and develop solutions that directly enhance our core products and user experience.
Build and Maintain a Scalable Data Infrastructure
Design and implement scalable, high-performance data infrastructure to support machine learning, analytics, and real-time data processing.
Continuously monitor and optimize data pipelines to ensure reliability, accuracy, and efficiency.

This is an exciting opportunity to blend data engineering and analysis in a pivotal full-stack role.

Youll be instrumental in ensuring our data's accuracy and availability, while also generating key insights to drive strategic decisions across Marketing, Product, R&D, Sales, and Customer Success. This role offers a unique chance to leverage both your technical skills and business understanding to extract actionable insights from complex data. Reporting directly to the CTO and collaborating with key stakeholders, youll have a significant impact on our data-driven culture.

Key Responsibilities

Own, maintain, and enhance data pipelines to guarantee data availability and quality.
Analyze and interpret complex data related to marketing, product performance, and user behavior.
Collaborate effectively with various teams to gather requirements, build data understanding, and communicate findings clearly.
Identify and resolve data discrepancies, defining the "source of truth" for crucial metrics.
Develop dashboards to monitor KPIs, assess performance against targets, and pinpoint areas for improvement.
Maintain user funnel dashboards, setting up alerts for anomalies and opportunities.
Implement proactive data monitoring and anomaly detection systems to ensure data accuracy and consistency.
Lead integrations with third-party platforms, optimizing data inputs for marketing tools and advertising platforms, potentially developing algorithms and triggers for targeted actions (e.g., engaging high-value, at-risk, or potential users).
Contribute to the development of our customer-facing Arena Analytics pipeline and data warehouse using tools like Fivetran, Snowflake, and ThoughtSpot.

We're looking for an experienced Data Engineer Team Lead to join our growing data group. In this role, youll not only design and implement high-scale, data-intensive platforms but also lead a team of talented engineers, driving the evolution of our data infrastructure. You will research and implement cutting-edge algorithmic solutions and collaborate with cross-functional teams on significant, high-impact projects that support our mission of providing accurate and actionable business intelligence.
Where does this role fit in our vision?
Every role at our company is designed with a clear purposeto integrate collective efforts into our shared success, functioning as pieces of a collective brain. Data is at the heart of everything we do. Our data engineers are responsible for building the core products that drive our business. The data teams own and manage the pipelines that create our assets, with a strong focus on the company KPIs.
What will you be responsible for?
Solve Complex Business Problems with Data Integration and Engineering Solutions
Develop and implement robust, scalable data pipelines and integration solutions within our Databricks-based environment.
Leverage technologies like Spark, Kafka, and Airflow to tackle complex data challenges and enhance business operations.
Design innovative data solutions that support millions of data points, ensuring high performance and reliability.
Collaborate with Business Stakeholders and Define Priorities
Partner with Product Managers, Data Scientists, and other key stakeholders to prioritize data initiatives that directly impact our core product offerings and user experience.
Ensure data solutions align with business goals, helping drive product features that bring value to our users and streamline B2B sales processes.

Required Staff Algo Data Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Staff Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
About Algo platform:
The objective of the algo platform group is to own the existing algo platform (including health, stability, productivity and enablement), to facilitate and be involved in new platform experimentation within the algo craft and lead the platformization of the parts which should graduate into production scale. This includes support of ongoing ML projects while ensuring smooth operations and infrastructure reliability, owning a full set of capabilities, design and planning, implementation and production care.
The group has deep ties with both the algo craft as well as the infra group. The group reports to the infra department and has a dotted line reporting to the algo craft leadership.
The group serves as the professional authority when it comes to ML engineering and ML ops, serves as a focal point in a multidisciplinary team of algorithm researchers, product managers, and engineers and works with the most senior talent within the algo craft in order to achieve ML excellence.
How youll make an impact:
As a Staff Algo Data Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet
Our tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.

Required Data Infra Tech Lead
A day in the life and how youll make an impact:
Were seeking an experienced and skilled Data Infra Tech Lead to join our Data Infrastructure team and drive the companys data capabilities at scale.
As the company is fast growing, the mission of the data infrastructure team is to ensure the company can manage data at scale efficiently and seamlessly through robust and reliable data infrastructure. As a tech lead, you are required to independently lead the design, development, and optimization of our data infrastructure, collaborating closely with software engineers, data scientists, data engineers, and other key stakeholders. You are expected to own critical initiatives, influence architectural decisions, and mentor engineers to foster a high-performing team.
You will:
Lead the design and development of scalable, reliable, and secure data storage, processing, and access systems.
Define and drive best practices for CI/CD processes, ensuring seamless deployment and automation of data services.
Oversee and optimize our machine learning platform for training, releasing, serving, and monitoring models in production.
Own and develop the company-wide LLM infrastructure, enabling teams to efficiently build and deploy projects leveraging LLM capabilities.
Own the company's feature store, ensuring high-quality, reusable, and consistent features for ML and analytics use cases.
Architect and implement real-time event processing and data enrichment solutions, empowering teams with high-quality, real-time insights.
Partner with cross-functional teams to integrate data and machine learning models into products and services.
Ensure that our data systems are compliant with the data governance requirements of our customers and industry best practices.
Mentor and guide engineers, fostering a culture of innovation, knowledge sharing, and continuous improvement.

We are looking for a talented Data Engineer to join our analytics team in the Big Data Platform group.
You will support our product and business data initiatives, expand our data warehouse, and optimize our data pipeline architecture.
You must be self-directed and comfortable supporting the data needs of multiple systems and products.
The right candidate is excited by the prospect of building the data architecture for the next generation of products and data initiatives.

This is a unique opportunity to join a team full of outstanding people making a big impact.
We work on multiple products in many domains to deliver truly innovative solutions in the Cyber Security and Big Data realm.

This role requires the ability to collaborate closely with both R&D teams and business stakeholders, to understand their needs and translate them into robust and scalable data solutions.

Key Responsibilities
Maintain and develop enterprise-grade Data Warehouse and Data Lake environments
Create data infrastructure for various R&D groups across the organization to support product development and optimization
Work with data experts to assist with technical data-related issues and support infrastructure needs
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for scalability
Build and maintain robust ETL/ELT pipelines for data ingestion, transformation, and delivery across various systems