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3 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an experienced and hands-on Backend Engineer to be a key player in building high-scale Data Platforms and Products for our business teams.
This role involves working with large datasets and scalable systems, and developing internal tools to enable data-driven decision-making across the company.
Key Responsibilities:
Develop internal tools for various teams.
Build and maintain microservices and APIs to support diverse workflows.
Operate in a real-time, event-driven environment.
Create and manage data pipelines.
Take ownership of multiple systems and products.
Develop and deploy machine learning pipelines to production in an event-driven architecture.
Work in a multi-cloud environment (Azure/GCP/AWS).
Integrate third-party tools with our platform.
Translate business requirements into technical specifications.
Our Tech Stack:
Python, BigQuery, Redis, RabbitMQ, MySQL, Tornado, SQLAlchemy, Airflow, Airbyte, NewRelic, Elastic, Kubernetes (K8S).
Requirements:
Experience: Minimum 5 years as a Backend Engineer.
Proficiency in Python: At least 5 years of experience, or expertise in an equivalent programming language.
Microservices and APIs: Proven experience in writing and maintaining microservices and REST APIs.
SQL Expertise: Strong proficiency in SQL.
Event-Driven Development: Hands-on experience with event-based development.
Big Data Experience: Familiarity with big data and high-velocity/volume systems is a plus.
Cloud Environments: Experience with multi-cloud environments (Azure, GCP, AWS).
This position is open to all candidates.
 
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3 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for an experienced and hands-on Backend Engineer to be a key player in building high-scale Data Platforms and Products for our business teams.
This role involves working with large datasets and scalable systems, and developing internal tools to enable data-driven decision-making across the company.
Key Responsibilities:
Develop internal tools for various teams.
Build and maintain microservices and APIs to support diverse workflows.
Operate in a real-time, event-driven environment.
Create and manage data pipelines.
Take ownership of multiple systems and products.
Develop and deploy machine learning pipelines to production in an event-driven architecture.
Work in a multi-cloud environment (Azure/GCP/AWS).
Integrate third-party tools with our platform.
Translate business requirements into technical specifications.
Our Tech Stack:
Python, BigQuery, Redis, RabbitMQ, MySQL, Tornado, SQLAlchemy, Airflow, Airbyte, NewRelic, Elastic, Kubernetes (K8S).
Requirements:
Experience: Minimum 5 years as a Backend Engineer.
Proficiency in Python: At least 5 years of experience, or expertise in an equivalent programming language.
Microservices and APIs: Proven experience in writing and maintaining microservices and REST APIs.
SQL Expertise: Strong proficiency in SQL.
Event-Driven Development: Hands-on experience with event-based development.
Big Data Experience: Familiarity with big data and high-velocity/volume systems is a plus.
Cloud Environments: Experience with multi-cloud environments (Azure, GCP, AWS).
This position is open to all candidates.
 
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23/03/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Senior Backend Engineer - Data Platform to join our expanding team and play a crucial role in designing, building, and maintaining robust and scalable data pipelines and infrastructure. In this role, you will directly enable data-driven decision-making and support the development and deployment of AI/ML products that power Health.

Youll collaborate closely with engineering, product, and data science teams to ensure our data systems are high-quality, resilient, and scalable as we grow. As a Senior Backend Engineer on our Data Platform team, you will drive efforts to deliver reliable, efficient, and consistent data services across the organization. You will also help enable the rapid development and deployment of advanced features, insights, and AI-driven capabilities that improve outcomes for clinicians and clients.

Who are you?
You are a seasoned backend or data engineer with experience working on production-grade ML/AI-powered products. You thrive in fast-paced, high-ownership environments and are passionate about building scalable and reliable systems. You understand the unique requirements of delivering AI/ML features in production, and you are comfortable working with modern technologies in the LLM/RAG ecosystem.
You pride yourself on delivering high-quality solutions quickly, without sacrificing design or reliability. Youre known for your responsiveness, collaborative spirit, and service-oriented mindset-especially when youre on-call and the stakes are high.How will you contribute?
Design, implement, and maintain scalable and reliable data pipelines and backend systems supporting both operational and analytical needs, with a focus on ML/AI product enablement.
Ensure data processing is optimized for speed, efficiency, and fault tolerance, enabling seamless integration with AI/ML workflows and reliable performance across all our Health products.
Monitor and improve uptime, reliability, and observability of our data infrastructure and pipelines.
Build and maintain systems to ensure data quality, consistency, and usability across the organization, enabling advanced analytics and AI solutions.
Work closely with product and engineering teams to deliver new features rapidly and with a high standard of technical excellence.
Drive innovation in how we build, measure, and optimize data features, backend services, and AI product integrations.
Participate in on-call rotations with a service-oriented approach and fast responsiveness.
Lead scalability efforts to support increasing data volumes, expanding AI/ML initiatives, and new product launches.
Requirements:
What qualifications and skills will help you to be successful?
At least 5 years of experience with Python in backend or data engineering roles, designing and operating large-scale data pipelines, backend services, and data infrastructure in production environments.
Hands-on experience working on ML/AI-powered products in production, with strong understanding of requirements for integrating data platforms with AI features.
Familiarity with modern LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) technologies, and experience supporting their deployment or integration.
Familiar with or have worked with these technologies (or alternatives):
Data Processing & Streaming: Apache Spark, DBT, Airflow, Airbyte, Kafka
API Development: FastAPI, micro-service architecture, SFTP
Data Storage: Data Lakehouse architectures, Apache Iceberg, Vector Databases, RDS
ML/AI: ML/LLM libraries and frameworks (such as Gemini, Hugging Face, etc.)
Cloud Infrastructure: AWS stack (S3, Firehose, Lambda, Athena, etc.), Kubernetes (K8s)
Demonstrated ability to optimize performance and ensure high availability, scalability, and reliability of backend/data systems.
Strong foundation in best practices for data quality, governance, security, and observability.
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
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 infrastructure-someone 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 stacks-its 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 lakes-designed 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.
Requirements:
2-4 years in software / solution or infrastructure engineering, with 2-4 years focused on building / maintaining large-scale data pipelines / storage & database solutions.
Proficiency in Trino, Spark (Structured Streaming & batch) and solid working knowledge of Apache Kafka.
Coding background in Python (must-have); familiarity with Bash and scripting tools is a plus.
Deep understanding of data storage architectures including SQL, NoSQL, and HDFS.
Solid grasp of DevOps practices, including containerization (Docker), orchestration (Kubernetes), and infrastructure provisioning (Terraform).
Experience with distributed systems, stream processing, and event-driven architecture.
Hands-on familiarity with benchmarking and performance profiling for storage systems, databases, and analytics engines.
Excellent communication skills-youll be expected to explain your thinking clearly, guide customer conversations, and collaborate across engineering and product teams.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.

This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutions-including the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.

What Youll Do

Architecture & Strategy

Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.

Engineering & Delivery

Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.

Leadership & Collaboration

Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.
Requirements:
What Were Looking For:
6-10+ years of experience in Data Engineering, with demonstrated architectural ownership.
Expert-level experience with Snowflake (mandatory), including performance optimization, data modeling, security, and ecosystem components.
Expert proficiency in SQL and strong Python skills for pipeline development and automation.
Experience with modern orchestration tools (Airflow, Dagster, Prefect, or equivalent).
Strong understanding of ELT/ETL patterns, distributed processing, and data lifecycle management.
Familiarity with streaming/event technologies (Kafka, Kinesis, Pub/Sub, etc.).
Experience implementing data quality, observability, and lineage solutions.
Solid understanding of cloud infrastructure (AWS, GCP, or Azure).
Strong background in DataOps practices: CI/CD, testing, version control, automation.
Proven leadership in driving architectural direction and mentoring engineering teams.

Nice to Have:
Experience with data governance or metadata management tools.
Hands-on experience with DBT, including modeling, testing, documentation, and advanced features.
Exposure to machine learning pipelines, feature stores, or MLOps.
Experience with Terraform, CloudFormation, or other IaC tools.
Background designing systems for high scale, security, or regulated environments.
This position is open to all candidates.
 
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30/03/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We are looking for a talented Data Engineer to join our analytics team in the Big Data Platform group.
Job Id: 25380
You will support our product and business data initiatives, expand our data warehouse, and optimize our data pipeline architecture with an AI first attitude.
The ideal candidate is experienced in leveraging AI tools as part of modern data pipeline development, enabling scalable solutions, accelerating delivery, and continuously exploring new approaches and technologies.
The right candidate is excited by the prospect of building the data architecture for the next generation of products and data initiatives.
This is a unique opportunity to join a team full of outstanding people making a big impact on us.
We work on multiple products in many domains to deliver truly innovative solutions in the Cyber Security and Big Data realm.
This role requires the ability to collaborate closely with both R&D teams and business stakeholders, to understand their needs and translate them into robust and scalable data solutions.
Key Responsibilities
Maintain and develop enterprise-grade Data Warehouse and Data Lake environments
Create data infrastructure for various R&D groups across the organization to support product development and optimization
Work with data experts to assist with technical data-related issues and support infrastructure needs
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for scalability
Build and maintain robust ETL/ELT pipelines for data ingestion, transformation, and delivery across various systems
Incorporate AI-assisted tools into data pipeline design, development, and optimization to improve efficiency, scalability, and innovation
Requirements:
B.Sc. in Engineering or a related field
3+ years of experience as a Data Engineer working on production systems
Advanced SQL knowledge and experience with relational databases
Proven experience using Python
Hands-on experience building, optimizing, and automating data pipelines, architectures, and data sets
Experience in creating and maintaining ETL/ELT processes
Strong project management and organizational skills
Strong collaboration skills with both technical (R&D) and non-technical (business) teams
Experience using AI tools as part of the data engineering workflow, with a mindset of experimentation, working at scale, and exploring new technologies
Advantage: Azure data services, Databricks, EventHub, and Spark.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from an office.

We are looking for a talented Data Engineer to help build and enhance the data platform that supports analytics, operations, and data-driven decision-making across the organization. You will work hands-on to develop scalable data pipelines, improve data models, ensure data quality, and contribute to the continuous evolution of our modern data ecosystem.

Youll collaborate closely with Senior Engineers, Analysts, Data Scientists, and stakeholders across the business to deliver reliable, well-structured, and well-governed data solutions.


What Youll Do:

Engineering & Delivery

Build, maintain, and optimize data pipelines for batch and streaming workloads.

Develop reliable data models and transformations to support analytics, reporting, and operational use cases.

Integrate new data sources, APIs, and event streams into the platform.

Implement data quality checks, testing, documentation, and monitoring.

Write clean, performant SQL and Python code.

Contribute to improving performance, scalability, and cost-efficiency across the data platform.

Collaboration & Teamwork

Work closely with senior engineers to implement architectural patterns and best practices.

Collaborate with analysts and data scientists to translate requirements into technical solutions.

Participate in code reviews, design discussions, and continuous improvement initiatives.

Help maintain clear documentation of data flows, models, and processes.

Platform & Process

Support the adoption and roll-out of new data tools, standards, and workflows.

Contribute to DataOps processes such as CI/CD, testing, and automation.

Assist in monitoring pipeline health and resolving data-related issues.
Requirements:
What Were Looking For

2-5+ years of experience as a Data Engineer or similar role.

Hands-on experience with Snowflake (mandatory)-including SQL, modeling, and basic optimization.

Experience with dbt (or similar)-model development, tests, documentation, and version control workflows.

Strong SQL skills for data modeling and analysis.

Proficiency with Python for pipeline development and automation.

Experience working with orchestration tools (Airflow, Dagster, Prefect, or equivalent).

Understanding of ETL/ELT design patterns, data lifecycle, and data modeling best practices.

Familiarity with cloud environments (AWS, GCP, or Azure).

Knowledge of data quality, observability, or monitoring concepts.

Good communication skills and the ability to collaborate with cross-functional teams.


Nice to Have:

Exposure to streaming/event technologies (Kafka, Kinesis, Pub/Sub).

Experience with data governance or cataloging tools.

Basic understanding of ML workflows or MLOps concepts.

Experience with infrastructure-as-code tools (Terraform, CloudFormation).

Familiarity with testing frameworks or data validation tools.

Additional Skills:

Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Security-First Mindset, User Experience (UX).
This position is open to all candidates.
 
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30/03/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We seek a skilled Infra Backend Engineer to join our R&D office in Tel Aviv, working in a hybrid and flexible model.

Youll collaborate with a top-tier R&D team and take your professional growth to the next level. Our backend infra teams work mainly with Python and Go, but we welcome talented backend engineers from any language background.

Key Responsibilities:

Build and optimize data pipelines handling large volumes of streaming and batch data in real time with high reliability and low latency.

Design, develop, and maintain backend services responsible for integrating with a wide variety of APIs, webhooks, and partners.

Own features end-to-end architecture, implementation, deployment and monitoring.

Ensure data accuracy and consistency across ingestion, transformation, and storage layers.

Collaborate with product, data engineering, and customer-facing teams to understand edge cases, fix production issues, and improve partner integrations.

Integrate and leverage top industry technologies such as Kafka, Iceberg, DynamoDB, Postgres, EMR, Kubernetes, Druid, Snowflake, and more.
Requirements:
What You Bring

3+ years of hands-on experience in backend development.

Strong proficiency in Python, Go, or similar backend languages.

Hands-on experience with REST APIs, third-party API integrations.

Experience with SQL/NoSQL databases and structured/unstructured data handling.

Strong debugging skills, ability to work with large datasets, and curiosity to dive deep into complex data issues.

Positive attitude, ownership mindset, and ability to work in a fast-paced environment.


Bonus points for:

Experience with AdTech/MarTech, attribution, or data analytics systems.

Knowledge of ETL/ELT orchestration tools or event-driven architectures.

Experience with Big Data or High Scale pipelines/ Projects.
This position is open to all candidates.
 
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03/03/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a skilled Senior Backend Engineer to join our team and help us build Cognition, a multi-agent AI platform. The ideal candidate will have strong backend engineering expertise and enthusiasm for working with cutting-edge AI technologies.You'll be responsible for designing and implementing backend services that integrate AI capabilities including large language models (LLMs), retrieval-augmented generation (RAG), and conversational interfaces into our consumer-facing products. This is an opportunity to expand your expertise into AI while leveraging your strong engineering foundation.
What Youll Do:
Design and develop scalable, high-performance backend services and APIs
Implement integrations with AI platforms and services
Work with AI specialists to translate AI capabilities into production-ready features
Ensure high reliability, performance, and security of AI-powered systems
Collaborate with product and engineering teams to gather requirements and deliver solutions
Requirements:
Proven Backend Expertise: 5+ years of professional experience, with astrong foundation in building and maintaining robust backend systems for large-scale consumer or enterprise products.
Technical Mastery: Advanced proficiency in at least one modern backend language (TypeScript and Node.js), with hands-on experience developing production-grade APIs and microservices. Experience with Lambda functions is a big plus.
Scalable Systems Builder: Demonstrated experience architecting and delivering high-availability services and distributed systems, leveraging patterns for reliability, performance, and security.
Cloud-Native Engineering: Deep familiarity with cloud platforms (AWS, GCP, or Azure), including hands-on experience with serverless technologies (e.g., AWS Lambda), infrastructure-as-code, and automated deployment pipelines.
Data Fluency: Solid experience with both SQL and NoSQL databases; knowledge of vector databases and embedding/search technologies is a big plus.
AI Platform Integration: Experience integrating with modern AI services (OpenAI, Hugging Face, etc.), and enthusiasm for collaborating with ML/AI specialists to bring LLMs, RAG, and conversational AI capabilities into production.
Results-Oriented Delivery: A track record of shipping consumer-facing features at scale, collaborating closely with both product and engineering teams.
Forward-Thinking Problem Solver: Eager to explore new technologies, solving complex problems using both solid engineering fundamentals and innovative approaches.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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תודה על שיתוף הפעולה
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Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group. 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 our data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives us 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.
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
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 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.
דרישות:
8+ years of experience in data-related roles such as Data Engineer, Data Infrastructure Engineer, BI Engineer, or Machine Learning Platform Engineer, with significant experience in at least two of these areas
A B.Sc. in Computer Science or a related technical field (or equivalent experience)
Extensive expertise in designing and implementing Data Lakes and Data Warehouses, including strong skills in data modeling and building scalable storage solutions
Proven experience in building large-scale data infrastructures, including both batch processing and streaming pipelines
A deep understanding of Machine Learning infrastructure, including tools and frameworks that enable Data Scientists to efficiently develop, deploy, and maintain models in production, an advantage
Proficiency in Python, Pulumi/Terraform, Apache Spark, AWS, Kubernetes (K8s), and Kafka for building scalable, reliable, and high-performing data solutions
Strong knowledge of databases, including SQL (schema design, query optimization) and NoSQ המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
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30/03/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
Required ML Data Engineer
Israel: Tel Aviv/ Hybrid (Israel)
R&D | Full Time | Job Id: 24792
Key Responsibilities
Your Impact & Responsibilities:
As a Data Engineer - AI Technologies, you will be responsible for building and operating the data foundation that enables our LLM and ML research: from ingestion and augmentation, through labeling and quality control, to efficient data delivery for training and evaluation.
You will:
Own data pipelines for LLM training and evaluation
Design, build and maintain scalable pipelines to ingest, transform and serve large-scale text, log, code and semi-structured data from multiple products and internal systems.
Drive data augmentation and synthetic data generation
Implement and operate pipelines for data augmentation (e.g., prompt-based generation, paraphrasing, negative sampling, multi-positive pairs) in close collaboration with ML Research Engineers.
Build tagging, labeling and annotation workflows
Support human-in-the-loop labeling, active learning loops and semi-automated tagging. Work with domain experts to implement tools, schemas and processes for consistent, high-quality annotations.
Ensure data quality, observability and governance
Define and monitor data quality checks (coverage, drift, anomalies, duplicates, PII), manage dataset versions, and maintain clear documentation and lineage for training and evaluation datasets.
Optimize training data flows for efficiency and cost
Design storage layouts and access patterns that reduce training time and cost (e.g., sharding, caching, streaming). Work with ML engineers to make sure the right data arrives at the right place, in the right format.
Build and maintain data infrastructure for LLM workloads
Work with cloud and platform teams to develop robust, production-grade infrastructure: data lakes / warehouses, feature stores, vector stores, and high-throughput data services used by training jobs and offline evaluation.
Collaborate closely with ML Research Engineers and security experts
Translate modeling and security requirements into concrete data tasks: dataset design, splits, sampling strategies, and evaluation data construction for specific security use.
Requirements:
3+ years of hands-on experience as a Data Engineer or ML/Data Engineer, ideally in a product or platform team.
Strong programming skills in Python and experience with at least one additional language commonly used for data / backend (e.g., SQL, Scala, or Java).
Solid experience building ETL / ELT pipelines and batch/stream processing using tools such as Spark, Beam, Flink, Kafka, Airflow, Argo, or similar.
Experience working with cloud data platforms (e.g., AWS, GCP, Azure) and modern data storage technologies (object stores, data warehouses, data lakes).
Good understanding of data modeling, schema design, partitioning strategies and performance optimization for large datasets.
Familiarity with ML / LLM workflows: train/validation/test splits, dataset versioning, and the basics of model training and evaluation (you dont need to be the primary model researcher, but you understand what the models need from the data).
Strong software engineering practices: version control, code review, testing, CI/CD, and documentation.

Ability to work independently and in collaboration with ML engineers, researchers and security experts, and to translate high-level requirements into concrete data engineering tasks. 
Nice to Have 
Experience supporting LLM or NLP workloads, including dataset construction for pre-training / fine-tuning, or retrieval-augmented generation (RAG) pipelines. 
Familiarity with ML tooling such as experiment tracking (e.g., Weights & Biases, MLflow) and ML-focused data tooling (feature stores, vector databases). 
Background in security / cyber domains (logs, alerts, incidents, SOC workflows) or other high-volume, high-variance data environments. 
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8597480
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שירות זה פתוח ללקוחות VIP בלבד