דרושים » דאטה » Senior Backend Data Engineer

We are looking for an experienced and visionary Data Engineer to help design, build, and scale our BI platform.
In this role, you will be responsible for developing our data analytics platform - enabling scalable data pipelines and robust data modeling to support real-time and batch analytics to provide 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 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.
Design and architect data products, from ingestion 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, Databricks, Power BI, and streaming platforms.
Collaborate cross-functional 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 looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

Were hiring an AI Backend Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of AI/ML/Backend engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

Required Senior Data Engineer
Description
We are making the future of Mobility come to life starting today.
We support the worlds largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.
At the heart of our platform lies the data infrastructure, driving advanced machine learning models and optimization algorithms. As the owner of data pipelines, you'll tackle diverse challenges spanning optimization, prediction, modeling, inference, transportation, and mapping.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platform-supporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do:
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.

We are looking for a Data Engineer to join our team and play a key role in designing, building, and maintaining scalable, cloud-based data pipelines. You will work with AWS services , Airflow and databricks to integrate, process, and analyze large datasets, ensuring data reliability and efficiency.
Your work will directly impact business intelligence, analytics, and data-driven decision-making across the company.
What Youll Do:
ETL & Data Processing: Develop and maintain ETL processes, integrating data from various sources (APIs, databases, external platforms) using Python, SQL, and cloud technologies.
Utilize LangGraph and other frameworks to create state of the art AI agents that integrate various tools and data sources.
Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead.
Data Modeling: Design and maintain logical and physical data models to support business needs.
Optimization & Scalability: Improve process efficiency and optimize runtime performance to handle large-scale data workloads.
Collaboration: Work closely with BI analysts and business stakeholders to define data requirements and functional specifications.
Monitoring & Troubleshooting: Ensure data integrity and reliability by proactively monitoring pipelines and resolving issues.

Were looking for an experienced Software Engineer to join the Cato DataSec team. In this critical role, you will join a team of experienced engineers building the next generation of Data Security platform. You will design and develop large-scale backend systems that process massive amounts of security data, build data pipelines, and enable advanced analytics and AI-driven security capabilities.

Responsibilities
Design and develop scalable backend services and data-intensive applications.
Build and maintain large-scale data pipelines that process and analyze massive volumes of security data.
Own features end-to-end, from architecture and backend implementation to production deployment.
Work closely with Product Management, Research, Data Science, SOC, NOC, and Automation teams to deliver new capabilities.
Design and implement enterprise-grade platform solutions with a focus on scalability, reliability, and performance.
Research and adopt new technologies to improve data processing, analytics, and AI-driven security products.
Collaborate with multiple engineering teams across the organization.

a central part of the R&D department is seeking a versatile Senior Data Engineer to take part in leading data vision using a lake-house architecture, and building high-scale solutions for handling and consuming the different data assets of the company.
In this role youll go beyond traditional boundaries, taking on full product responsibilities - from conceptualization and architecture to design, maintenance, and continuous development. You will collaborate closely with stakeholders across the company to ensure our solutions effectively meet their needs.
The ideal candidate will have strong data engineering capabilities, along with software development skills including understanding of designing and managing AWS cloud infrastructure and strong knowledge of different data architectures, methods and tools.
Responsibilities:
Design and development of scalable, reliable, and secure data infrastructure and build ETL pipelines that handle diverse clinical data for research. Write production SQL, Spark jobs and craft schemas that evolve gracefully as research and production questions change.
Automate releases with CI/CD and Infrastructure as Code.
Optimise throughput, latency and cloud cost to meet research timelines at large scale.
Develop and maintain high-quality, scalable, and efficient code while fostering a culture of continuous improvement through regular retrospectives and knowledge sharing.
Take ownership of the full development lifecycle, including requirement gathering, design, implementation, testing, deployment, and ongoing maintenance.
Collaborate with cross-functional teams, including data scientists, data analysts, product managers, regulatory teams, and other developers, to drive the development of new tools and features that support mission.
Explore and adopt new technologies and frameworks that can enhance the capabilities of the Data-Nexus team and the overall data projects .

We are currently expanding our R&D center in Tel Aviv, where we are building advanced data systems, automation infrastructure, and intelligent workflows that power our products and enable the next wave of innovation in advertising technology.

This role focuses on building reliable data systems and automation infrastructure, while helping us introduce AI-driven and agentic automation capabilities that improve how our engineering and data platforms operate.

What You Will Do
Design and build backend services using Node.js and TypeScript
Develop and maintain data pipelines and automated workflows
Work with Snowflake, MongoDB, and large datasets
Improve reliability and performance of data processing systems
Build and maintain automation infrastructure that supports data and platform operations
Design systems that help automate engineering and data workflows
Write unit and integration tests for backend services and workflows
Collaborate with analysts and product teams to translate complex workflows into scalable systems
Participate in improving engineering standards, testing culture, and development practices
Drive the next generation of automation across the platform by designing AI-driven and agentic workflows that enhance how our engineering and data systems operate
Your Day-to-Day Work
Developing backend services and APIs
Optimizing queries and data processing workflows
Building reliable systems for processing large-scale data
Designing and implementing automation processes across data and engineering workflows
Supporting AI-driven and agentic automation initiatives across internal systems
Writing automated tests to ensure system stability
Collaborating with engineers in Israel and global teams

We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
Key Responsibilities:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

we are using technology to transform transportation around the world. From changing a single persons daily commute to reducing humanitys collective environmental footprint - weve got huge goals.
As a Senior Backend Engineer in the Routing team, you will be responsible for designing, building, and scaling the backend systems that power our companys core products. Youll work on high-impact, distributed services that manage geospatial data, large-scale databases, real-time events, and mission-critical workflows used across multiple teams and regions. Your work will directly influence system reliability, performance, and developer productivity at scale.
You will collaborate closely with Product, Infrastructure, Data, and other engineering teams to define system boundaries, evolve shared services, and ensure our backend platform can support rapid product growth. You will be part of a highly skilled and motivated engineering group responsible for building robust, scalable, and maintainable backend systems that operate in real time and at high load.
What Youll Do:
Design, build, and scale backend systems and data pipelines that power our companys GIS and mapping platform, from initial design through production deployment and long-term ownership.
Own features end-to-end with strong accountability, including design, implementation, testing, deployment, monitoring, and ongoing maintenance.
Develop and maintain Python-based data pipelines that ingest, process, and transform large-scale OpenStreetMap (OSM) and other geospatial datasets.
Model, store, and query complex geospatial data using PostgreSQL and PostGIS, including road topology, zones, polygons, points, and other business-critical spatial entities.
Optimize database schemas, spatial indexes, and queries to efficiently handle large datasets and high-throughput workloads.
Build and maintain backend services and APIs that expose geospatial and mapping data to other backend services, frontend applications, and data consumers.
Collaborate closely with other backend teams, frontend teams, data teams, and infrastructure to align on data contracts, system boundaries, and cross-team initiatives.
Improve system reliability, observability, and performance through monitoring, alerting, benchmarking, and continuous optimization.
Contribute to architectural decisions, technical standards, and best practices, while mentoring other engineers and raising the overall engineering bar.