דרושים » דאטה » Experienced Data Engineer

We are looking for an exceptional Big Data Engineer to join our R&D team. This is a unique opportunity for a recent graduate or early-career engineer to enter the world of Big Data. You will work alongside the best engineers and scientists in the industry to develop systems that process and analyze data from around the digital world.
So what will you be doing all day?
Learn and Build: Assist in the design and implementation of high-scale systems using a variety of technologies, mentored by senior engineers.
Collaborate: Work in a data research team alongside data engineers, data scientists, and data analysts to tackle data challenges.
Optimize: Help improve the existing infrastructure of code and data pipelines and learn how to identify and eliminate bottlenecks.
Innovate: Experiment with various technologies in the domain of Machine Learning and big data processing.
Monitor: Assist in maintaining monitoring infrastructure to ensure smooth data ingestion and calculation.

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.

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 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.

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 Senior Algo Data Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Senior 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 Senior Algo Data 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.

Were looking for a Senior Data Engineer to join our Data team - someone whos passionate about building reliable, scalable data infrastructure and thrives on solving complex technical challenges.
In this role, youll own the design and development of end-to-end data pipelines that power analytics and data-driven decision-making.
Youll collaborate closely with both business and technical stakeholders to ensure data flows smoothly, accurately, and efficiently across the company.
What You Will Do:
Design, implement, and maintain large-scale ETL and ELT pipelines using modern data frameworks and cloud technologies.
Work with Redshift data warehouses to design efficient schemas and optimize performance.
Build and manage data ingestion processes from multiple sources - APIs, SaaS platforms, internal systems, and databases.
Collaborate with stakeholders to deliver clean, well-modeled, and high-quality data.
Build and evolve a modern, efficient, and scalable data warehouse architecture.
Ensure observability, monitoring, and testing across all data processes.
Apply best practices in CI/CD, version control (Git), and data quality validation.

We are seeking an experienced Senior data Engineer to join our dynamic data team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure, ensuring the availability, reliability, and quality of our data. This role requires strong technical expertise, problem-solving skills, and the ability to collaborate across teams to deliver data -driven solutions.Key Responsibilities:
* Design, implement, and maintain robust, scalable, and high-performance data pipelines and ETL processes.
* Develop and optimize data models, schemas, and Storage solutions to support analytics and Machine Learning initiatives.
* Collaborate with software engineers and product managers to understand data requirements and deliver high-quality solutions.
* Ensure data quality, integrity, and governance across multiple sources and systems.
* Monitor and troubleshoot data workflows, resolving performance and reliability issues.
* Evaluate and implement new data technologies and frameworks to improve the data platform.
* Document processes, best practices, and data architecture.
* Mentor junior data engineers and contribute to team knowledge sharing.

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 Lemonades data ecosystem.

The groups mission is to build a state-of-the-art Data Platform that drives Lemonade 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 Lemonade 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 BI Data Engineer to join our Data team within the Information Systems group.
In this role, you will be responsible for building and maintaining scalable, high-quality data pipelines, models, and infrastructure that support business operations across the entire company, with a primary focus on GTM domains.
You will take ownership of core data architecture components, ensuring data consistency, reliability, and accessibility across all analytical and operational use cases.
Your work will include designing data models, orchestrating transformations, developing internal data applications, and ensuring that business processes are accurately represented in the data.
This role requires a combination of deep technical expertise and strong understanding of business operations.
You will collaborate closely with analysts, domain experts, and engineering teams to translate complex business processes into robust, scalable data solutions. If you are passionate about data architecture, building end-to-end data systems, and solving complex engineering challenges that directly impact the business wed love to meet you!
Key Responsibilities:
Design, develop, and maintain end-to-end data pipelines, ensuring scalability, reliability, and performance.
Build, optimize, and evolve core data models and semantic layers that serve as the organizations single source of truth.
Implement robust ETL/ELT workflows using Snowflake, dbt, Rivery, and Python.
Develop internal data applications and automation tools to support advanced analytics and operational needs.
Ensure high data quality through monitoring, validation frameworks, and governance best practices.
Improve and standardize data modeling practices, naming conventions, and architectural guidelines.
Continuously evaluate and adopt new technologies, features, and tooling across the data engineering stack.
Collaborate with cross-functional stakeholders to deeply understand business processes and translate them into scalable technical solutions.

We are looking for a talented Architect to join us. As a Data Architect, you will be the organizational point of contact for all things related to data persistence and architecture. You will work closely with engineering teams across the Product, Platform, and Data groups to design, govern, and evolve our data models, databases, and data-related systems. Your goal will be to ensure scalability, reliability, security, and efficiency for all data storage and retrieval across the organization.
A few of the things you will do:
Be the primary point of contact and subject matter expert for data persistence across the entire engineering organization.
Define and govern the data architecture strategy, standards, and best practices for relational, NoSQL, and data warehouse systems.
Partner with engineering teams from product, platform, and data groups to design and implement scalable and robust data models for new and existing services.
Lead the design and optimization of the organizations data flows. You will help to ensure that data moves efficiently, consistently, and with high quality across all systems and domains.
Evaluate and recommend new technologies and data solutions to meet evolving business needs.
Drive initiatives to improve data quality, consistency, and integrity across all production systems, from ideation to hands-on execution.
Establish, maintain, and communicate documentation for all data models and architectural decisions.