לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER בתל אביב יפו

We are looking for an experienced Data Engineering Team Leader.
In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
A day in the life and how youll make an impact:
Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.

Own accuracy and coverage of detection capabilities such as: technology fingerprinting, SSO/login identification, vulnerability-to-technology mapping
Build AI-powered workflows (LLM classifiers, automated rule generation) to scale detection beyond manual rule-writing
Design eval frameworks and feedback loops - golden datasets, precision/recall tracking, regression testing - to keep quality high as automation grows
Tune IP/domain discovery logic: decision rules, blacklists, thresholds, unstructured data parsing
Extend BI pipelines and schemas to enrich asset data
Investigate customer-reported detection gaps; root-cause and fix systematically

we are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will be helping us design and build a flexible and scalable system that will allow our business to move fast and innovate. You will be expected to show ownership and responsibility for the code you write, but it doesn't stop there. you are encouraged to think big and help out in other areas as well.
Responsibilities:
Designing and writing code that is critical for business growth
Mastering scalability and enterprise-grade SAAS product implementation
Sense of ownership - leading design for new products and initiatives as well as integrating with currently implemented best-practices
Building and owning production-grade ETL/ELT pipelines that power analytics, ML training, and real-time AI systems
Designing data architectures that support agentic systems, including:
Embeddings and vector-based retrieval
RAG pipelines
Feedback loops and continuous improvement
Review your peer's design and code
Work closely with product managers, peer engineers, and business stakeholders

Required Data Engineer
Tel Aviv, Israel
About us:
We are international Multi-Cloud experts, utilizing the power of the cloud for smart digital transformation. With 5 sites over 4 continents around the globe, +450 experts, +1000 customers, and +30 years of proven experience, our mission is to deliver the best Multi-Cloud service to our customers, accelerate their business and help them grow. As tech-savvies, To help our customers stay on top of their game, our teams are constantly developing new strategies and tools that will help them improve cloud performance, spending, visibility, control, and automation. Our cloud experts will make any digital transformation a quick, smart, and easy process
What You'll Do:
Design, build, and maintain data pipelines and infrastructure
Develop and implement data quality checks and monitoring processes
Work with engineers to integrate data into our systems and applications
Collaborate with scientists and analysts to understand their data needs.

We are looking for a Senior Data & Machine Learning Engineer to operate at the intersection of data platform engineering and machine learning enablement. This role is responsible for building scalable, efficient, and reliable data systems while enabling Data Science and Analytics teams to develop and deploy ML-driven features.

You will take ownership of the data and ML infrastructure layer, ensuring that pipelines, storage models, and compute usage are optimized, while also shaping how data workflows and ML solutions are designed across the organization.


Responsibilities
Data Platform & Infrastructure

Design, build, and maintain scalable data pipelines and storage systems supporting analytics and ML use cases
Ensure compute and cost efficiency across pipelines, storage models, and processing workflows
Own and improve data orchestration, transformation, and serving layers (e.g., Spark, DBT, streaming/batch systems)
Build and maintain shared infrastructure components, including:
IO managers and data access abstractions
Integrations with DBT, Spark, and other data frameworks
Internal tooling to improve developer productivity and reliability
ML Enablement & Collaboration

Partner closely with Data Science to design and productions ML solutions for new features and research initiatives
Translate experimental models into robust, scalable production systems
Support feature engineering, training pipelines, and inference workflows
Help define best practices for ML lifecycle management (training, validation, deployment, monitoring)
Data Quality, Governance & Best Practices

Enforce best practices for building and maintaining data processes across Data Analyst and Data Science teams
Define standards for:
Data modeling and transformations
Pipeline reliability and observability
Testing, versioning, and documentation
Improve data quality, consistency, and discoverability across the organization
Performance & Reliability

Optimize systems for performance, scalability, and cost efficiency
Monitor and troubleshoot data pipelines and ML systems in production
Implement observability (logging, metrics, alerting) across data workflows

Required Research Infra Engineer
The Dream Job
As a Research Infra Engineer, you will build and operate the shared platforms that power our cyber research: data ingestion, connectivity to internal/external systems, scalable analysis environments, and self-serve tools which allow the team moving faster.
Youll partner closely with CyberAI researchers to translate research needs into reliable, secure, cloud-deployed capabilities used across the group. Your goals are to reduces research-toil, improves reproducibility and code quality, and accelerates the path from prototype to shared capability.
The Dream-Maker Responsibilities
Design, implement, and iterate on internal platforms that support research workflows (e.g., data ingestion, enrichment, indexing, search, labeling, evaluation harnesses, experiment tooling).
Develop durable pipelines and connectors to bring in and normalize research data sources.
Create reusable libraries, templates, CLIs, and services that enable researchers to run analyses and experiments safely and repeatably.
Own deployments, reliability, observability, access control, and cost/performance of the research stack so its usable by all researchers.
Work closely with CyberAI researchers on the development of next-generation artificial cyber researchers and AI-driven analysis capabilities.

we are looking for a Senior Solutions Architect, Public Sector.
As a Solutions Architect at AWS, youll build technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey.
Youll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging projects.
Internally, you will be the voice of the customer, sharing their needs and wants to inform the roadmap of AWS features.
Key job responsibilities:
In this role, your creativity will link technology to tangible solutions, with the opportunity to define or invent cloud-native reference architectures for a variety of use cases.
You will participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts) and evangelize and educate about AWS technology (e.g. through workshops, user groups, meetups, public speaking, online videos or conferences).
If you can educate AWS customers about the art of the possible, while challenging the impossible, come build the future with us.
This role is within the Israel organization and you would be working with Public Sector customers.

Realize your potential by joining the leading performance-driven advertising company!
As a Senior Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Senior Algo Data Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

Realize your potential by joining the leading performance-driven advertising company!
As a Staff Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Staff Algo Data Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

Were looking for a Senior Data Engineer to own high-impact data products from architecture through production deployment, monitoring, and continuous improvement. This isnt a pure infrastructure role - youll combine strong engineering with product thinking, operational excellence, and awareness of data quality, cost, and business impact.
You will design, implement, test, deploy, and maintain production-grade data products - pipelines, transformation layers, data quality and reliability systems - using tools like DBT (on Spark) and Databricks. Youll apply best practices in Python and SQL to build scalable and maintainable data transformations, and leverage technologies like LLMs and GenAI to create innovative solutions for real business problems.
This role is ideal for someone who wants technical leadership responsibilities in an AI-first engineering culture - we use LLMs, GenAI, and AI-native development tools as core parts of our daily workflow.
Key Responsibilities:
Act as a technical leader within the team - raise engineering standards, drive strong architectural choices, and improve how we build
Own data products end-to-end: design, development, deployment, monitoring, and iteration
Work closely with senior leadership to translate strategic goals into scalable data solutions
Develop and maintain production ETL/ELT pipelines using DBT (on Spark) and orchestrated workflows in Databricks
Build monitoring, alerting, and testing pipelines to ensure reliability and performance in production
Evaluate and introduce new technologies - including AI-native development tools - and integrate the ones that create real impact
Collaborate with customers and external data providers - gathering requirements and making product decisions.
Mentor team members through code reviews, pairing, and knowledge sharing

We are looking for a Senior Data Engineer to join our Platform group in the Data Infrastructure team.
Youll work hands-on to design and deliver data pipelines, distributed storage, and streaming services that keep our data platform performant and reliable. As a senior individual contributor you will lead complex projects within the team, raise the bar on engineering best-practices, and mentor mid-level engineers - while collaborating closely with product, DevOps and analytics stakeholders.
About the Platform group
The Platform Group accelerates our productivity by providing developers with tools, frameworks, and infrastructure services. We design, build, and maintain critical production systems, ensuring our platform can scale reliably. We also introduce new engineering capabilities to enhance our development process. As part of this group, youll help shape the technical foundation that supports our entire engineering team.
Job responsibilities:
Code & ship production-grade services, pipelines and data models that meet performance, reliability and security goals
Lead design and delivery of team-level projects - from RFC through rollout and operational hand-off
Improve system observability, testing and incident response processes for the data stack
Partner with Staff Engineers and Tech Leads on architecture reviews and platform-wide standards
Mentor junior and mid-level engineers, fostering a culture of quality, ownership and continuous improvement
Stay current with evolving data-engineering tools and bring pragmatic innovations into the team.

we are seeking a Senior Data Infra Engineer. You will be responsible for designing and building all data, ML pipelines, data tools, and cloud infrastructure required to transform massive, fragmented data into a format that supports processes and standards. Your work directly empowers business stakeholders to gain comprehensive visibility, automate key processes, and drive strategic impact across the company.

Responsibilities

Design and Build Data Infrastructure: Design, plan, and build all aspects of the platform's data, ML pipelines, and supporting infrastructure.
Optimize Cloud Data Lake: Build and optimize an AWS-based Data Lake using cloud architecture best practices for partitioning, metadata management, and security to support enterprise-scale operations.
Lead Project Delivery: Lead end-to-end data projects from initial infrastructure design through to production monitoring and optimization.
Solve Integration Challenges: Implement optimal ETL/ELT patterns and query techniques to solve challenging data integration problems sourced from structured and unstructured data.

We are seeking a Senior Data Engineer to join our R&D organization as part of a backend-oriented team, responsible for building and scaling the core data infrastructure.
In this role, you will design and develop data pipelines that stream and process data directly from production systems. You will play a key role in shaping our data platform, building robust, scalable infrastructure and pipelines using modern technologies, and working hands-on with both new components and existing systems.
Responsibilities
Collaborate as a strong team player within a dynamic, cross-functional environment
Design, develop, and maintain scalable data models, Lakehouse architectures, pipelines, and ETL processes
Enhance data workflows to support efficient real-time and batch processing
Work closely with cross-functional teams to understand data requirements and deliver impactful solutions
Stay up to date with the latest data engineering technologies and best practices, continuously improving our data platform.

We are looking for an ML Engineer / MLOps Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.
You will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. Youll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle management-the foundation of our product.
Responsibilities:
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.
End-to-end ML delivery - enabling model performance development, training, validation, testing, and version control.
Build and support monitoring and observability tools - dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as: Feature Store, Vector / Graph Databases.
Data wrangling - supporting and enabling data requirements for research, training, validation, and testing.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.

At our company, Israels first fully digital bank, were building the technology that powers a new era of intuitive, transparent, people-first banking. As our platform grows and our services expand, were looking for a team leader to lead a data engineering team.
The team is responsible for ingestion, processing, and serving bronze level data to other analytic teams in the organization.
In this role, you will define the data architecture of our unified Data Lakehouse, own all ETL and streaming operations, define governance processes and implement tools, make sure our data is fresh, accurate and whole always.
Your Day-to-Day
Menor and lead a team of 4-6 data engineers.
Own sensitive data operations, including monitoring, on-call and production operations.
Build and manage all ETL and streaming operations related to the Data Lakehouse.
Develop, maintain, and optimize robust data pipelines and integrations across multiple systems.
Build a platform for other analytic teams to build data products on top of the Data Lakehouse.
Define and implement quality and governance processes to make sure data is fresh, accurate and whole.
Collaborate with engineering, BI, and business teams to translate requirements into scalable data solutions
Work hands-on with data orchestration, transformation, and cloud infrastructure (OCI, Snowflake, AWS)
Support implementation of best practices in data management and observability.