לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER

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).

Our Data team consists of highly skilled senior software and data professionals who collaborate to solve complex data challenges. We process billions of records daily from multiple sources using diverse infra and multi-stage pipelines with intricate data structures and advanced queries, and complex BI.

A bit about our infrastructure. Our main databases are Snowflake, Iceberg on AWS, and Trino. Spark on EMR processes the huge influx of data. Airflow does most of the ETL.

The data we deliver drives insights both for internal and external customers. Our internal customers use it routinely for decision-making across the organization, such enhancing our product offerings.

What Youll Do
Build, maintain, and optimize data infrastructure.
Contribute to the evolution of our AWS-based infrastructure.
Work with database technologies - Snowflake, Iceberg, Trino, Athena, and Glue.
Utilize Airflow, Spark, Kubernetes, ArgoCD and AWS.
Provide AI tools to ease data access for our customers.
Integrate external tools such as for anomaly detection or data sources ingestion.
Use AI to accelerate your development.
Assures the quality of the infra by employed QA automation methods.

seeking a skilled and motivated Data Scientist. This individual will play a pivotal role in identifying key data points for collection, developing strategies to accumulate data and deriving actionable insights an anomaly based on a solid foundation of relevant know-how. Also, will also be responsible for creating, testing, and deploying scripts and methods for data collection and analysis to support decision-making. The Engineer will collaborate with cross-functional teams to identify critical data sources to determine the most effective data collection strategies, will develop automated and scalable data collection pipelines, will ensure data quality, integrity, and consistency across all sources and may use AI techniques to refine the results toward failures predictions.

We are looking for a DataOps Engineer to own the infrastructure that powers our large-scale data processing platform. This is a platform-facing role sitting at the intersection of data engineering and infrastructure - you'll be the person who makes Spark run reliably and efficiently on Kubernetes, so that data engineers can build with confidence.
You understand data workloads deeply enough to make smart infrastructure decisions, and you have the production instincts to keep complex systems healthy at scale. If you get excited about shaving minutes off Spark job runtimes, right-sizing cluster autoscalers, and building the internal tooling that makes a data platform feel effortless, this role is for you.
RESPONSIBILITIES:
Design, deploy, and operate the Kubernetes-based infrastructure that runs Apache Spark and large-scale data processing workloads
Own the reliability, performance, and cost-efficiency of the data platform - including SLAs, autoscaling, resource quotas, and workload isolation
Manage Spark-on-K8s configurations, Airflow infrastructure, and Databricks integration; tune for throughput, latency, and cost
Build and maintain CI/CD pipelines and infrastructure-as-code for data platform components
Develop observability tooling - metrics, logging, alerting, and data quality dashboards - to proactively surface issues across the pipeline stack
Collaborate closely with Data Engineers to understand workload patterns and translate them into infrastructure decisions
Manage cloud storage (GCS/S3), Delta Lake, and Unity Catalog infrastructure
Drive platform improvements end-to-end: from design through deployment and ongoing ownership.

we are where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps, FinOps, and GenAI support that drives real results.
We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.
Were looking for a Senior Data Architect to help shape how high-growth startups build and scale on AWS. In this role, youll design and deliver end-to-end data and analytics solutions - from architecture and pipelines to visualization and insights - guiding customers from concept through production. Youll work closely with startup founders, technical leaders, and account executives to create scalable, cost-efficient architectures that drive real business impact.
Work location - hybrid from Tel Aviv
If you are interested in this opportunity, please submit your CV in English.
Key Responsibilities
Design, develop, and implement data & analytics solutions to meet business requirements and create cost-efficient, highly available, and scalable customer solutions, including Well-Architected reviews and SoW.
Research and analyze current solutions and initiate improvement plans.
Collaborate with other engineers and stakeholders to ensure solutions are designed and developed according to best practices.
Lead workshops, POCs, and architecture reviews with startup customers, conferences, webinars, and more.
Stay up to date on Data Engineering and Analytics trends and contribute to internal enablement.
Frequent travels - locally (on-demand to meet with customers and partners and attend local events) and abroad (at least once a quarter).

We're seeking a Mid to Senior Data Engineer to join our Cloud Identity & Perimeter, a critical component of security infrastructure. Our team develops and maintains complex data pipelines that process billions of records daily, analyzing identity-related security patterns, effective permissions, internet exposure, and attack paths. We're at the forefront of securing enterprise identities and delivering actionable security insights at scale.

What You'll Do:

Design and implement high-performance, distributed data processing pipelines handling petabytes of security data

Architect complex data transformations using Apache Spark for large-scale batch and stream processing

Be part of shaping new products while collaborating with product teams, customers, and sales.

Build and optimize real-time data streaming solutions using Kafka for identity analytics

Develop and maintain scalable ETL processes that handle billions of daily events

Create efficient data models for complex security analytics queries

Collaborate with cross-functional teams to deliver high-impact security features

Optimize query performance and data storage patterns for large-scale distributed systems

Participate in system design discussions and architectural decisions

We're seeking a Mid to Senior Data Engineer to join our Cloud Identity & Perimeter, a critical component of security infrastructure. Our team develops and maintains complex data pipelines that process billions of records daily, analyzing identity-related security patterns, effective permissions, internet exposure, and attack paths. We're at the forefront of securing enterprise identities and delivering actionable security insights at scale.

What You'll Do:

Design and implement high-performance, distributed data processing pipelines handling petabytes of security data

Architect complex data transformations using Apache Spark for large-scale batch and stream processing

Be part of shaping new products while collaborating with product teams, customers, and sales.

Build and optimize real-time data streaming solutions using Kafka for identity analytics

Develop and maintain scalable ETL processes that handle billions of daily events

Create efficient data models for complex security analytics queries

Collaborate with cross-functional teams to deliver high-impact security features

Optimize query performance and data storage patterns for large-scale distributed systems

Participate in system design discussions and architectural decisions

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.

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.

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.

Ready to lead the way in building our next-gen data platforms? Join us and shape the future of secure connectivity!
We are looking for a Data Engineering Team Leader with deep expertise in building and managing data pipelines and streaming architecture.
Job Id: 24787
This role is ideal for an experienced and proactive leader with strong technical skills in distributed systems and data platforms. You will drive the architecture, design, and development of scalable data ingestion and processing solutions. This is an exciting opportunity to join a growing product in an enterprise environment with significant impact and room for professional growth.
This job is located in Tel Aviv (hybrid).
About Us:
Were creating the industrys leading SASE platform, merging advanced security with seamless connectivity. Our mission is to empower businesses to thrive in a cloud-first world, and data is at the heart of this transformation.
Key Responsibilities:
Inspire and mentor a top-tier data engineering team to deliver mission-critical solutions
Architect and optimize data ingestion, enrichment, and storage for massive scale and reliability
Collaborate with cross-functional teams to ensure seamless integration and data availability
Define best practices and enforce engineering excellence across the data domain.

Required Data Engineer
Israel: Tel Aviv/ Hybrid (Israel)
R&D | Full Time | Job Id: 25316
Why Join Us?
We are building next-generation GenAI security intelligence and SaaS Security Posture Management (SSPM) solutions that protect enterprises worldwide. If you enjoy turning complex security data into actionable insights and delivering end-to-end systems, this role is for you.
About the role:
You will own, build, and maintain our Pythonic data pipeline and enrichment system on top of PostgreSQL and BigQuery. This system powers security analytics, detections, and intelligence. A core part of your job will be to design and implement new components, improve reliability and performance, and ensure data quality and observability.
Key Responsibilities:
Own, build, and maintain production data pipelines and enrichment services using Python, PostgreSQL, and BigQuery.
Architect data systems end to end, including design, deployment, monitoring, and iterative improvement.
Analyze complex security datasets and SaaS telemetry to uncover risks, patterns, and opportunities.
Research emerging threat vectors and contribute to automated intelligence feeds and published reports.
Work across security domains such as SSPM, Shadow Integrations, DLP, and GenAI Protection.

Our Senior Data Engineer will play an essential role by building the underlying infrastructures, collecting, storing, processing and analyzing large sets of data, while collaborating with researchers, architects, and engineers, in order to design and build high-quality data processing for our flows.

In this role, you are responsible for end-to-end development of the data pipeline and data models, working with major data flow that includes structured and unstructured data. You will also hold responsibility for operating parts of our production system. Your focus will be on developing and integrating systems that retrieve and analyzing data that influence people's lives. This role for our Tel Aviv office is a hybrid role working at least two days per week in the office.

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

Were hiring a Machine Learning Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across Stamplis 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 ML 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 our 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.