דרושים » דאטה » Data Engineer

we are looking for a 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.

Required Senior Data Engineer
The opportunity
Join our dynamic Data & ML Engineering team in iAds and play a pivotal role in driving data solutions that empower data science, finance, analytics, and R&D teams. As an Experienced Data Engineer, you'll work with cutting-edge technologies to design scalable pipelines, ensure data quality, and process billions of data points into actionable insights.
Success Indicators:
In the short term, success means delivering reliable, high-performance data pipelines and ensuring data quality across the product. Long-term, you'll be instrumental in optimizing workflows, enabling self-serve analytics platforms, and supporting strategic decisions through impactful data solutions.
Impact:
Your work will directly fuel business decisions, improve data accessibility and reliability, and contribute to the team's ability to handle massive-scale data challenges. You'll help shape the future of data engineering within a global, fast-paced environment.
Benefits and Opportunities
You'll collaborate with talented, passionate teammates, work on exciting projects with cutting-edge technologies, and have opportunities for professional growth. Competitive compensation, comprehensive benefits, and an inclusive culture make this role a chance to thrive and make a global impact.
What you'll be doing
Designing and developing scalable data pipelines and ETL processes to process massive amounts of structured and unstructured data.
Collaborating with cross-functional teams (data science, finance, analytics, and R&D) to deliver actionable data solutions tailored to their needs.
Building and maintaining tools and frameworks to monitor and improve data quality across the product.
Providing tools and insights that empower product teams with real-time analytics and data-driven decision-making capabilities.
Optimizing data workflows and architectures for performance, scalability, and cost efficiency using cutting-edge technologies like Apache Spark and Flink.

We are looking for a Data Engineer to join our team and help advance our Apps solution. Our product is designed to provide detailed and accurate insights into Apps Analytics, such as traffic estimation, revenue analysis, and app characterization. The role involves constructing and maintaining scalable data pipelines, developing and integrating machine learning models, and ensuring data integrity and efficiency. You will work closely with a diverse team of scientists, engineers, analysts, and collaborate with business and product stakeholders.
Key Responsibilities:
Develop and implement complex, innovative big data ML algorithms for new features, working in collaboration with data scientists and analysts.
Optimize and maintain end-to-end data pipelines using big data technologies to ensure efficiency and performance.
Monitor data pipelines to ensure data integrity and promptly troubleshoot any issues that arise.

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.

We are seeking a skilled Data/ Backend Engineer to design and implement complex, high-scale systems that retrieve, process, and analyze data from the digital world. This role involves developing and maintaining backend infrastructure, creating robust data pipelines, and ensuring the seamless operation of data-driven products and services.
Key Responsibilities:
- Design and build high-scale systems and services to support data infrastructure and production systems.
- Develop and maintain data processing pipelines using technologies such as PySpark, Hadoop, and Databricks.
- Implement dockerized high-performance microservices and manage their deployment.
- Monitor and debug backend systems and data pipelines to identify and resolve bottlenecks and failures.
- Work collaboratively with data scientists, analysts, and other engineers to develop and maintain data-driven solutions.
- Ensure data is ingested correctly from various sources and is processed efficiently.

We are looking for a brilliant, quick-learner Data Engineer for our data engineering team - an independent, logical thinker who understands the importance of data structuring for macro-business decisions.
The position combines high technical skills with a business orientation.
It involves working closely with the analysts, product, and the R&D team and directly affecting the company's cross-department decisions.
Our Data Engineer should be able to design and build a data flow from the API or source requirements with the most suitable tools to fit the data product requirements.
They need to speak in technical and practical terms and, more importantly, lead from one to the other while dealing with challenges, independent learning, and creating them to make our team even better.
Roles and Responsibilities:
Designing and building full data pipelines: From defining source structures to delivering clean, organized data ready for analysis, your work ensures analysts have everything they need to make smart, data-driven decisions
Translating business needs into scalable data solutions involves staying close to the roadmap, understanding technical nuances, and delivering purpose-built pipelines and tools
Writing high-quality, maintainable code: Following best practices while leveraging modern data engineering tooling and CI/CD principles
Solving complex data challenges creatively: Whether it's device identity (Device Graph), online-to-offline matching, privacy compliance, or server-to-server integrations
Managing multi-source data environments: We bring in data from over 50 sources (Marketing, Product, CS, CRM, Ops, and more), and you will assist in tying it all together into a reliable, insight-ready system
Keeping quality and reliability top of mind: Monitor, validate, and improve data quality while ensuring robust processes across the stack

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 aspectsensuring 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.

Req ID: 20718

As part of the Data Infrastructure group, youll help build Lemonades data platform for our growing stack of products, customers, and microservices.

We ingest our data from our operational DBs, telematics devices, and more, working with several data types (both structured and unstructured). Our challenge is to provide building tools and infrastructure to empower other teams leveraging data-mesh concepts.

In this role youll:
Help build Lemonades data platform, designing and implementing data solutions for all application requirements in a distributed microservices environment.

Build data-platform ingestion layers using streaming ETLs and Change Data Capture.

Implement pipelines and scheduling infrastructures.

Ensure compliance, data-quality monitoring, and data governance on Lemonades data platform.

Implement large-scale batch and streaming pipelines with data processing frameworks.

Collaborate with other Data Engineers, Developers, BI Engineers, ML Engineers, Data Scientists, Analysts and Product managers.

Share knowledge with other team members and promote engineering standards.

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.

Realize your potential by joining the leading performance-driven advertising company!
As a Data Engineer on our Business Analytics & Business Intelligence Group in Tel Aviv Office, youll play a vital role on all aspects of the data, from ETL processes to optimizing our Business data models and infrastructure.
How youll make an impact:
As a Data Engineer, youll bring value by:
Have end to end ownership: Design, develop, deploy, measure and maintain our Business data infrastructure, ensuring high availability, high scalability and efficient resource utilization.
Lead the BI Engineering domain, including mentoring BI Engineers, establishing best practices, and driving BI engineering strategy.
Automate data workflows to streamline processes, reducing manual efforts and improving accuracy of our BI infrastructure..
Collaborate with other departments (e.g., IT/Data, R&D, Product, IS) to ensure seamless integration of BI tools with other systems and data models.
Work closely with the BI Development team to develop, maintain, and automate operational and executive-level reports and dashboards that offer actionable insights.
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our data pipelines.
Excellent communication and collaboration skills to work across teams.