דרושים » דאטה » Big Data Engineer

Join us as a Data Engineer to help develop and maintain our rapidly growing data platform. You will be responsible for implementing scalable data pipelines, contributing to the development of custom tools, and ensuring massive datasets are processed efficiently to drive critical business decisions.
Responsibilities:
Implement and maintain scalable, production-grade data pipelines and infrastructure that support analytics and new product features.
Build and contribute to internal software and tooling that improves data team workflows, focusing on driving structure, maintainability, and engineering best practices.
Develop and manage key components of our new data platform, ensuring high reliability, performance, and scalability.
Work closely with security researchers, data analysts, and product teams to translate innovative cybersecurity ideas into functional, production-ready data solutions.
Apply and support best practices in data quality, governance, and observability to ensure our data systems remain robust and trustworthy as we scale.

Required Data Engineering Manager
Description
We are one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make peoples lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions.
As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.
If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!
Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

We are looking for an experienced Data Infrastructure Team Lead to lead our Data Infrastructure team. In this role, you will have formal people-management responsibility for a multidisciplinary team that builds, productionizes, and improves big data and analytics infrastructure. You will be responsible for team delivery, combining technical depth, agile leadership, and an AI-first mindset to help the team build reliable systems, improve how it works, and continuously raise its engineering standards.

Location: Ramat Gan (Bursa area), Israel - Hybrid model

What will you do?

Lead, manage, and develop a data infrastructure team of approximately 5-7 people.
Take responsibility for team delivery, including planning, prioritization, execution, and continuous improvement.
Lead agile ways of working, including scrum-based delivery practices.
Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure.
Partner closely with cross-functional stakeholders across technical, scientific, and business interfaces.
Help the team adopt AI-first engineering practices, including automation and AI-assisted development workflows.
Drive improvements in team processes, technical quality, delivery predictability, and collaboration.
Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems.
Create an environment where team members can grow, contribute, and improve together.

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

We are looking for a highly skilled and versatile Senior Backend Engineer to join our development team. As a Senior Backend Engineer, you will be responsible for designing, developing, and maintaining the backend infrastructure and components of our platform. As part of your role, you will also work on the frontend aspects of our platform and collaborate with stakeholders and cross-functional teams to optimize full-cycle system performance.
Responsibilities:
Design, develop, and maintain backend systems and APIs to support our web applications.
Implement and optimize data storage solutions, including databases, to ensure efficient and reliable data management.
work closely with front-end developers to integrate backend functionalities and ensure a seamless user experience.
Collaborate with product managers, stakeholders, and cross-functional teams to gather requirements, translate them into technical specifications, troubleshoot and resolve backend-related issues, and optimize system performance.

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
** The role includes working on-site at our Jerusalem office several days per week.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

We are looking for a highly skilled and versatile Backend Engineer to join our development team. As a Backend Engineer, you will be responsible for designing, developing, and maintaining the backend infrastructure and components of our platform. As part of your role, you will also work on the frontend aspects of our platform and collaborate with stakeholders and cross-functional teams to optimize full-cycle system performance
Responsibilities:
Design, develop, and maintain backend systems and APIs to support our web applications
Implement and optimize data storage solutions, including databases, to ensure efficient and reliable data management
work closely with front-end developers to integrate backend functionalities and ensure a seamless user experience
Collaborate with product managers, stakeholders, and cross-functional teams to gather requirements, translate them into technical specifications, troubleshoot and resolve backend-related issues, and optimize system performance

we are looking for a Solution Engineer.
The Demand Forecasting team is at a pivotal, high-growth stage. This role is highly dynamic, requiring a blend of technical depth and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities:
Lead and support customer-facing Demand Forecasting use cases from discovery through deployment
Work hands-on with customer data to design, test, and validate forecasting solutions
Act as a trusted analytical and technical advisor to customers, deeply understanding their business context and datasets
Analyze and explain model outputs and complex analytical concepts in a clear, business-oriented way
Troubleshoot technical and data-related challenges and drive them to resolution
Collaborate closely with Data Science and Customer Success teams, providing structured feedback from customer use cases
Help customers achieve measurable business impact and adoption of Demand Forecasting module