דרושים » הנדסה » Senior Data Engineer

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.

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.

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

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.

Were looking for a versatile, talented, and highly motivated Data Engineer to join our growing team.

If youre passionate about solving complex problems, thrive in dynamic environments, and love working at the intersection of data engineering, machine learning infrastructure, and AI innovation, this role is for you.

As a Data Engineer, youll play a key role in shaping how data flows through the company, from building scalable pipelines and robust infrastructure to powering data science models and enabling internal teams with intelligent GenAI-powered tools. This is a hands-on, high-impact role with plenty of room for ownership, creativity, and growth.

This is a high-impact role where your work will shape how the company leverages data and AI. If you want to build, innovate, and push boundaries in a collaborative and fast-moving environment, wed love to meet you.

Responsibilities
Own the entire data lifecycle from understanding business needs and building reliable pipelines to ensuring data quality, observability, and performance.
Design, build, and scale modern data infrastructure including data lakes, warehouses, and complex ETL/ELT pipelines.
Integrate and consolidate diverse data sources (CRMs, APIs, databases, SaaS platforms) into a single, trusted source of truth.
Implement and manage CI/CD, observability, and infrastructure-as-code in a cloud-native environment.
Work with the data science team on their ML pipelines, giving data scientists the infrastructure and automation they need to deploy models to production with speed and confidence.
Collaborate with cross-functional teams to embed GenAI agents into business processes, creating smart workflows that boost efficiency and reduce manual work.
Develop frameworks and internal tooling that empower other teams to safely adopt AI and accelerate innovation.
Optimize data infrastructure for performance and cost-efficiency, with a focus on BigQuery optimization.
Ensure high data quality and integrity across large-scale ETL processes. Work closely with analysts, data scientists, and product managers to support data modeling, governance, and analytical initiatives.

We are seeking a passionate and highly skilled Senior Golang Developer to join our dynamic Software Engineering team. The ideal candidate is an expert Go engineer with a strong background in building scalable, high-performance distributed backend systems on the cloud. You should be enthusiastic about working with cutting-edge technologies in an Agile environment and capable of owning complex components end-to-end, taking an idea through design, testing, and production monitoring.
What will you do:
Responsible for the full lifecycle of our distributed services, focusing on performance, reliability, and innovation: Design & Development
* Architect, design, and implement robust backend services and distributed system components using Go, ensuring high scalability, reliability, and performance.
* Develop microservices and server side infrastructure with clean, maintainable, and testable code.
*  system Ownership: Take full ownership of complex components, moving them from initial concept design through development, testing, CI/CD, and production deployment and monitoring. system Optimization & data
* Optimize service performance, parallel processing, concurrency handling, and resource utilization in high-scale environments.
* Work with a variety of data stores and event-streaming technologies.
* Integrate services with technologies like OpenSearch, Redis, and column store databases as part of the system architecture.
* Implement secure development practices and production ready standards. Collaboration & DevOps
* Work closely with data Engineering, DevOps, and Product teams to deliver high quality, production grade services.
* Develop and deploy applications in Kubernetes environments, leveraging strong DevOps best practices and CI/CD pipelines for smooth, reliable releases.
* Participate actively in code reviews, design discussions, and cross team technical initiatives. Innovation
* Explore new technologies, evaluate tools, and propose improvements to the existing stack and development processes, championing a culture of continuous improvement and technical excellence.

We are looking for an experienced BI / Data Engineer to develop systems that make vast amount of data more accessible and efficient throughout the organization. This is a perfect opportunity if youre passionate about data and have strong analytical and technical skills.

You will be developing innovative and creative ways to deliver data and information at scale in a fast-growing, exciting industry while working closely with our data analysts, product managers, software engineering teams, and management.

Responsibilities:

Design, manage, and optimize scalable data models and BI infrastructures for internal and external stakeholders
Work with diverse relational and non-relational databases (Presto, Athena, Firebolt, MySQL, etc.)
Build and maintain reliable ETL/ELT pipelines using Airflow, Python, and Upsolver
Design and develop data visualizations and dashboards (Tableau)
Identify and implement technological solutions for large-scale analytics
Serve as the central data authority, providing guidance, documentation, and support across the company

We are seeking a Data Engineering Lead to own and scale data platform infrastructure

Build our new data Lakehouse to support various product and business needs
Support cutting-edge AI Agents and cybersecurity use cases
Be part of the Data and AI Algorithms group
Collaborate closely with dev teams, AI/ML engineers, security researchers and business teams
Ensure the availability, reliability and quality of our data infrastructure
Help define best practices for data modeling and orchestration at scale

We are looking for a Backend Engineer to join our Data Engineering team and develop backend components and data-oriented infrastructure for large-scale data processing.

In this role, you will develop infrastructure that enables the generation and evolution of data entities and their reliable distribution across internal systems.

You will work closely with Data Science and Backend core teams to build scalable, cost-efficient, production-grade solutions in a data-heavy environment.



What you will do

Design and implement infrastructure that supports high-volume data processing
Continuously optimize performance, cost, and reliability at scale
Collaborate with Data Science and Backend core teams to define data contracts, interfaces, and integration patterns
Maintain high engineering standards testing, observability, clean code, CI/CD fundamentals

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 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