דרושים » דאטה » Senior Data Engineer

We are looking for an experienced and visionary Data Platform Engineer to help design, build and scale our BI platform from the ground up.

In this role, you will be responsible for building the foundations of our data analytics platform enabling scalable data pipelines and robust data modeling to support real-time and batch analytics, ML models and business insights that serve both business intelligence and product needs.

You will be part of the R&D team, collaborating closely with engineers, analysts, and product managers to deliver a modern data architecture that supports internal dashboards and future-facing operational analytics.

If you enjoy architecting from scratch, turning raw data into powerful insights, and owning the full data lifecycle this role is for you!

Responsibilities
Take full ownership of the design and implementation of a scalable and efficient BI data infrastructure, ensuring high performance, reliability and security.

Lead the design and architecture of the data platform from integration to transformation, modeling, storage, and access.

Build and maintain ETL/ELT pipelines, batch and real-time, to support analytics, reporting, and product integrations.

Establish and enforce best practices for data quality, lineage, observability, and governance to ensure accuracy and consistency.

Integrate modern tools and frameworks such as Airflow, dbt, Databricks, Power BI, and streaming platforms.

Collaborate cross-functionally with product, engineering, and analytics teams to translate business needs into data infrastructure.

Promote a data-driven culture be an advocate for data-driven decision-making across the company by empowering stakeholders with reliable and self-service data access.

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 infrastructuresomeone 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 stacksits 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 lakesdesigned 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.
Operate and debug object storebacked data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

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 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.
About the Platform group
The Platform Group accelerates our productivity by providing developers with tools, frameworks, and infrastructure services. We design, build, and maintain critical production systems, ensuring our platform can scale reliably. We also introduce new engineering capabilities to enhance our development process. As part of this group, youll help shape the technical foundation that supports our entire engineering team.
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.

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 the leader in hybrid-cloud security posture management, using the attackers perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. we are looking for a talented Senior data Engineer Join a core team of experts responsible for developing innovative cyber-attack techniques for Cloud-based environments (AWS, Azure, GCP, Kubernetes) that integrate into our fully automated attack simulation. About the Role: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.

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.

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.

About the Role: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.

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

Our platform ingests and processes data from operational databases, telematics, and diverse product sources. Youll build robust backend services and data processing pipelines, leveraging state-of-the-art frameworks and cloud-native solutions, all while collaborating with Data Engineers, ML Engineers, Analysts, and Product Managers to turn real-world needs into resilient systems.

In this role youll:
Design & Develop Backend Services: Lead the design and implementation of backend systems and APIs for our distributed data platform

Build Data Ingestion & Processing: Architect and develop scalable ingestion pipelines with streaming ETL, Change Data Capture, and large-scale batch and stream processing

Own Data Platform Infrastructure: Implement and optimize scheduling, workflow orchestration, and data governance tools to support high-quality, compliant data flows

Drive Engineering Standards: Establish and promote backend best practices, ensuring high reliability, code quality, and maintainability across the team

Cross-functional Collaboration: Work closely with data engineers, ML engineers, product managers, and analysts to translate business needs into scalable backend systems

Mentorship: Share your backend and infrastructure expertise by collaborating, reviewing, and mentoring fellow engineers.

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.