דרושים » דאטה » (OS) Senior data Engineer

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

We are looking for an Experienced Data Engineer to join our marketing team and take end-to-end ownership of our data platform and production data pipelines. In this role, you will be responsible for building robust, scalable, and observable data systems that power analytics, reporting, and downstream business use cases. You will work deeply hands-on with data infrastructure, modeling, and orchestration, and act as a key technical partner to Marketing, Sales Product and Business and Finance teams.
This role suits someone who enjoys working close to the metal, designing systems that scale, and solving ambiguous data problems in a dynamic startup environment. You will play a critical role in shaping how data flows through the company, setting engineering standards, and ensuring data is trustworthy, performant, and ready for growth.
What You'll Do:
Design, build, and maintain scalable, reliable data pipelines and data warehouse architectures to support analytics and business intelligence needs.
Own the end-to-end ETL/ELT processes - ingesting data from internal and external sources, transforming it, and making it analytics-ready.
Model and optimize data structures (fact tables, dimensions, semantic layers) to support performant querying and reporting.
Ensure high standards of data quality, integrity, observability, and reliability across all data assets.
Partner closely with Analytics, Product, Marketing, and Finance teams to understand data requirements and deliver robust data solutions.
Implement monitoring, alerting, and testing frameworks to proactively identify data issues.
Optimize warehouse performance and cost efficiency (query optimization, partitioning, clustering, etc.).
Identify gaps in data collection and work with engineering teams to improve instrumentation and data availability.
Support experimentation and analytics use cases by enabling clean, trustworthy datasets for A/B testing and analysis.
Document data models, pipelines, and best practices to support scale and knowledge sharing.

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.
We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.

Required Data Engineer II - GenAI
20718
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

Required Senior Data Engineer I - GenAI Foundation Models
21679
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

We are looking for a Senior Data Engineer to join our Engineering Team. You will play a crucial role in designing, developing, and optimizing data pipelines for blockchain and social data along with developing backend ETL infrastructure for our flagship product.
You will:
Be a key player in architecting and implementing our companys data pipelines.
Lead the end-to-end design of ETLs, data structure, database ingestion and management from the architectural phase through development to deployment in production.
Contribute to our companys real-time analytics product on our extensive data lake of blockchain and social data.
Use a diverse technology stack. Our current stack contains mainly: Python, Apache Iceberg, StarRocks, MongoDB, Trino, Spark, AWS Athena, Postgres and more.
Success in this role will be measured by your ability to independently oversee processes from start to finish, collaborate effectively with team members, deliver rapid and well-tested features, and contribute significantly to our overall business achievements.

We are seeking a talented Data Engineer to join our BI & Data team in Tel Aviv. You will play a pivotal role in building and optimizing the data infrastructure that powers our business. In this mid-level position, your primary focus will be on developing a robust single source of truth (SSOT) for revenue data, along with scalable data pipelines and reliable orchestration processes. If you are passionate about crafting efficient data solutions and ensuring data accuracy for decision-making, this role is for you.



Responsibilities:

Pipeline Development & Integration

- Design, build, and maintain robust data pipelines that aggregate data from various core systems into our data warehouse (BigQuery/Athena), with a special focus on our revenue Single Source of Truth (SSOT).

- Integrate new data sources (e.g. advertising platforms, content syndication feeds, financial systems) into the ETL/ELT workflow, ensuring seamless data flow and consolidation.

- Implement automated solutions for ingesting third-party data (leveraging tools like Rivery and scripts) to streamline data onboarding and reduce manual effort.

- Leverage AI-assisted development tools (e.g., Cursor, GitHub Copilot) to accelerate pipeline development

Optimization & Reliability

- Optimize ETL processes and SQL queries for performance and cost-efficiency - for example, refactoring and cleaning pipeline code to reduce runtime and cloud processing costs.

- Develop modular, reusable code frameworks and templates for common data tasks (e.g., ingestion patterns, error handling) to accelerate future development and minimize technical debt.

- Orchestrate and schedule data workflows to run reliably (e.g. consolidating daily jobs, setting up dependent task flows) so that critical datasets are refreshed on time.

- Monitor pipeline execution and data quality on a daily basis, quickly troubleshooting issues or data discrepancies to maintain high uptime and trust in the data.

Collaboration & Documentation

- Work closely with analysts and business stakeholders to understand data requirements and ensure the infrastructure meets evolving analytics needs (such as incorporating new revenue streams or content cost metrics into the SSOT).

- Document the data architecture, pipeline processes, and data schemas in a clear way so that the data ecosystem is well-understood across the team.

- Continuously research and recommend improvements or new technologies (e.g. leveraging AI tools for data mapping or anomaly detection) to enhance our data platforms capabilities and reliability and ensure our data ecosystem remains a competitive advantage.

We act as the central nervous system for engineering, enabling platform teams to unify their stack and expose it as a governed layer through golden paths for developers and AI agents.
By combining rich engineering context, workflows, and actions, we help organizations transition from manual processes to autonomous, AI-assisted engineering workflows while maintaining control and accountability.
As a product-led company, we believe in building world-class platforms that fundamentally shape how modern engineering organizations operate.
What youll do:
Lead the design and development of scalable and efficient data lake solutions that account for high-volume data coming from a large number of sources both pre-determined and custom.
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 a data lake that will serve our company's users.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Collaborate with cross-functional teams (product, analytics, and R&D) to enhance our company's data solutions.
Who youll work with:
Youll be joining a collaborative and dynamic team of talented and experienced developers where creativity and innovation thrive.
You'll closely collaborate with our dedicated Product Managers and Designers, working hand in hand to bring our developer portal product to life.
Additionally, you will have the opportunity to work closely with our customers and engage with our product community. Your insights and interactions with them will play an important role to ensure we deliver the best product possible.
Together, we'll continue to empower platform engineers and developers worldwide, providing them with the tools they need to create seamless and robust developer portals. Join us in our mission to revolutionize the developer experience!

We are seeking a seasoned R&D Group Manager to lead a group of talented engineers in designing and building scalable data pipelines and cloud-native applications. This role is perfect for an experienced and proactive person with outstanding leadership skills. The ideal candidate is a team player who has a passion for data processing and applications on a large scale. This is an incredible opportunity to join a growing product in an enterprise company with ample opportunities for professional growth.
This job is located in Tel Aviv (hybrid).
About Us
At our company, were building 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
Lead multiple teams designing and scaling real-time data pipelines and cloud-native applications
Work with cutting-edge technologies to build resilient, high-performance systems
Shape architecture and strategy in a fast-paced environment where your decisions impact thousands of users globally
Key Responsibilities
Inspire and mentor engineering teams to deliver mission-critical solutions for data infrastructure and backend services
Architect and oversee robust, scalable data pipelines and real-time processing systems
Drive design and implementation of microservices and serverless applications using AWS and Azure ADX
Collaborate with product managers, data scientists, and stakeholders to turn business needs into technical excellence
Foster a culture of innovation, ownership, and continuous improvement
Manage hiring, performance reviews, and career development for team members.

we are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will play a key role in shaping and driving our analytics data pipelines and solutions to empower business insights and decisions. Collaborating with a variety of stakeholders, you will design, develop, and optimize scalable, high-performance data analytics infrastructures using modern tools and technologies. Your work will ensure data is accurate, timely, and actionable for critical decision-making.
Key Responsibilities:
Lead the design, development, and maintenance of robust data pipelines and ETL processes, handling diverse structured and unstructured data sources.
Collaborate with data analysts, data scientists, product engineers and product managers to deliver impactful data solutions.
Architect and maintain the infrastructure for ingesting, processing, and managing data in the analytics data warehouse.
Develop and optimize analytics-oriented data models to support business decision-making.
Champion data quality, consistency, and governance across the analytics layer.