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Were looking for a Data Engineer to join our company. This is a hands-on, cross-functional role focused on owning and improving our data quality, pipeline reliability, and modeling infrastructure. Youll be responsible for managing and optimizing our DBT models, ETL processes, and data connectors - and will work closely with product, operations, and engineering teams to ensure data is accurate, consistent, and accessible.

You should be someone who thrives on autonomy, takes pride in clean and scalable solutions, and enjoys helping others get the data they need.

In this role you will
Architect our entire DBT project and data warehouse structure completely from scratch-a rare, high-impact opportunity
Lead data modeling efforts: Translating business needs into scalable, reliable data models
Build and monitor data pipelines and connectors from various internal and external systems
Ensure high standards of data quality, consistency, and documentation
Collaborate with engineering, product, and operations teams to understand needs and build data solutions
Proactively detect data issues and work to resolve them
Help define and improve internal data best practices and standards
Support data governance efforts and advocate for trustworthy, well-modeled data
You will be one of the pioneers of a new team - passion & energy is required

The Product group is looking for a Senior Product Manager to join the Exposures product team - fastest-growing emerging product. You will lead complex, advanced, AI-heavy cybersecurity features across multiple disciplines from initial rollout to iterative learning loops. You will manage high-level strategic initiatives, dive into technical details, and collaborate with global engineering, cyber research, sales, and marketing teams to scale enterprise software solutions.

Responsibilities
Define the product vision, build and maintain the product roadmap, and drive full-lifecycle execution for advanced, AI-heavy enterprise cyber features.
Work directly with customers to identify business needs, translate them into technical roadmap priorities, and optimize the customer experience.
Collaborate cross-functionally with Engineering, Cyber Research, Sales, and Marketing teams to deliver scalable software products to the global market.
Manage complex, cross-functional and interdisciplinary product dependencies across local and remote teams while mitigating delivery risks.

As a Senior Software Engineer specializing in the AI & ML ecosystem, you'll be a core contributor owning and evolving critical parts of AI ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Engineers and Data Scientists to harness speed and scale in the frameworks they already use.

We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with as a vector store, ML feature stores, and LLM-powered data applications.

columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real: building the robust, production-ready connectors that make the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do
Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
Drive the AI/LLM integration strategy: designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats? Do you thrive in the dynamic world of cybersecurity? If so, we invite you to join our innovative and forward-thinking team at Palo Alto Networks, where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers.
As a Senior Principal Data Scientist, you will be a technical leader and hands-on architect, bridging the worlds of advanced data science, robust software engineering, and next-generation AI. You will bring a deep, diverse background in classical machine learning algorithms alongside cutting-edge LLM agent architectures to build resilient, production-grade defense techniques against cyber-villains. Operating as a premier technical authority, you will drive the vision, design, and large-scale development of our groundbreaking, Agentix LLM-based security solutions that block attacks even before they begin.
Key Responsibilities
Serve as a hands-on technical compass for a diverse, elite product-oriented research team, pioneering state-of-the-art technologies and setting the engineering standards for AI/ML excellence across the organization.
Design, implement, and optimize robust Agentic LLM solutions and multi-agent workflows engineered to autonomously counter modern, sophisticated cyber threats.
Oversee and actively contribute to the entire end-to-end lifecycle, moving seamlessly from ambiguous research concepts and POCs to high-throughput, low-latency production deployments.
Build and enforce comprehensive frameworks for continuous real-time monitoring, evaluation, and guardrails to track model drift, latency, and agent behavior in production environments.
Decompose highly complex, multi-layered algorithmic problems into actionable technical roadmaps and strategic insights for both deeply technical engineers and executive business stakeholders.

As a Principal Data Engineer, you will be integral to the security research group, designing, building, and maintaining the data pipelines and data frameworks that are the backbone of our cyber attack detection capabilities. You will work closely with top security and AI researchers, enabling their work and seeing the direct impact of your contributions on our services and the day-to-day effectiveness of the research team.
Key Responsibilities
Lead the design and implementation of end-to-end, complex data pipelines and data platforms in cloud environment.
Collect, analyze, and translate complex data requirements from various stakeholders including data analysts, developers, and Cyber security researchers.
Develop robust, scalable Cloud based data solutions using Python and distributed processing frameworks such as Apache Beam (Dataflow) , GKE , Spark , etc.
Utilize AI as part of the development cycle, including generating, reviewing, and testing code via prompts.
Model and manage data within cloud MPP databases and data lakes such as BigQuery, Redshift, or Snowflake.

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 multi-stage pipelines with intricate data structures and advanced queries.

We are responsible for building data pipelines end to end-from raw data ingestion to the creation of actionable datasets-following the bronze, silver, and gold paradigm. This includes business logic, infrastructure, ETLs, optimization, and ongoing maintenance.

The data we deliver drives insights and decision-making across the organization and enhances our product offerings. We leverage technologies such as AWS, Snowflake, Iceberg, Airflow, Spark, and more.

What Youll Do

Lead the translation of business and product requirements into scalable data models, transformations, and pipelines.

Design and own datasets across bronze, silver, and gold layers, including defining grain, aggregations, and data contracts.

Develop and maintain SQL-heavy data pipelines and Airflow DAGs (workflow logic, dependencies, backfills, python, and lots of SQL).

Own data correctness for key business metrics (e.g., ARR), including deep root cause analysis and resolution of data issues.

Define and drive best practices for SQL, data modeling, and pipeline design across the team.

Optimize queries and data models for performance, scalability, and cost efficiency.

Collaborate closely with product managers, analysts, and BI developers to refine requirements and ensure high-quality data delivery.

Develop AI-agents to accelerate data analysis by internal and external users.

Work with complex data inputs (e.g., JSON, schemas, logs) and incorporate them into robust data pipelines.

As a Data Scientist, you will apply your expertise in software engineering, LLM agents, and cybersecurity to build new defense techniques against cyber-villains. You will be a driving force in designing and developing groundbreaking, Agentic LLM-based security solutions that block attacks before they begin. Join our innovative team to shape the future of cybersecurity and impact millions of customers.
Important: this role requires a unique combination of hands-on software engineering skills as well as previous experience with designing and delivering LLM-driven products.
Key Responsibilities
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach.
Design and implement agentic LLM solutions to face modern cybersecurity challenges.
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders.
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.

Were looking for a BI & Data Engineering Team Lead to join our BI team and take end-to-end ownership of high-impact analytics foundations while mentoring a team of 4-6 talented BI Data Engineers. This role sits at the core of how measures success, makes decisions, and scales-turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.

In this role, you'll combine people leadership with hands-on technical depth (roughly 30% of your time), owning the roadmap, architecture, and delivery of BI platform. Youll shape how AI and agentic workflows transform the way BI is built and consumed, helping raise the bar for analytics engineering across the company.

Hands-on experience using GenAI to improve analytics engineering workflows, automate development processes, and increase delivery speed is a must for this role.

This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

This might be for you if:

You enjoy owning data foundations end to end - from raw data to semantic layers while leading and growing people
You like turning ambiguous business questions into clear, governed metrics and scalable data models
You care about data quality, performance, and trust at scale, as well as optimization and FinOps practices
You enjoy mentoring, setting technical standards, and leading by example with a hands-on approach (~30%)
You actively leverage AI tools and agentic automations to improve development speed, analytical accuracy, and metric governance

The Data Group builds and maintains the core data assets that power our products, from our Company and Contact databases to our Connect and Recommendation systems. The Data Tech Lead sits at the forefront of that mission, leading engineering innovation that directly shapes the experience of our growing user base and drives the evolution of intelligent data services.

This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

Your impact and responsibilities:

Leading the design and development of scalable, high-performance data workflows, including both batch pipelines and real-time data products.
Defining, implementing, and enforcing engineering best practices related to code quality, testing, CI/CD pipelines, observability, and documentation.
Mentoring, supporting, and growing a team of data engineers, fostering a collaborative and high-performance engineering culture.
Identifying opportunities to create new data assets and features that expand product capabilities and value proposition.
Driving architectural decision-making in areas of data modeling, storage solutions, and compute resources within cloud environments such as Databricks and Snowflake.
Collaborating closely with cross-functional stakeholders- including Product, DevOps, and R&D - to ensure effective delivery and platform stability.
Promoting and championing a data-driven mindset across the organization, balancing technical rigor with business context and strategic goals.

CodeValue is looking for a Drools / DMN Expert to join a large-scale Enterprise project in the banking and financial services domain. The role focuses on business rules, decision management, and the design of complex decision logic that supports critical banking processes. What You'll Do
* Design and implement business rules using Drools.
* Model business decisions using DMN.
* Design and maintain Decision Tables.
* Translate complex business logic into maintainable rules.
* Separate business rules from application logic.
* Collaborate with analysts, architects, developers, and business stakeholders.
* Support the evolution and optimization of decision management solutions.
Location: Rishon LeZion Work Model: Hybrid – 4 day per week on-site

CodeValue is looking for an experienced Senior Business / System Analyst to join a large-scale Enterprise project in the banking and financial services domain. The role combines business analysis and technical analysis , working on complex Enterprise processes, Domains, Services, APIs, integrations, data models, and technical requirements. You will work closely with Architects, Developers, business stakeholders, and delivery teams to translate business needs into clear, scalable technical solutions. What You'll Do
* Analyze complex business and technical processes in a large-scale Enterprise environment.
* Break down business capabilities into Domains and Services
* Analyze system interactions, APIs, integrations, and data models.
* Define and document Business Flows and system processes.
* Translate business needs into clear functional and technical requirements.
* Define and maintain technical backlogs and requirements.
* Work closely with Architects, Developers, business stakeholders, and delivery teams.
* Identify dependencies and integration requirements across multiple systems.
* Support the design of scalable and maintainable Enterprise solutions.
* Participate in discussions around system design, architecture, and technical

Location: Rishon LeZion Work Model: Hybrid – 4 day per week on-site

What you will do
You will lead a team of experienced Data Scientists while remaining deeply involved in the technical work.

This is a hands-on leadership role (~70% hands-on) combining direct modeling work with ownership of team direction and execution.

You will work on core systems that operate at a massive scale, where:

Data is abundant, but labels are scarce and expensive

problems are long-tail and ambiguous

Systems must meet strict latency and cost constraints (pre-bid)

Your responsibilities include:

Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps

Design and build models across computer vision, NLP, and multimodal pipelines

Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment

Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)

Improve model quality (precision/recall) while balancing cost, latency, and scale

Drive automation systems (auto-labeling, auto-curation, retraining loops)

Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems

Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward

Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems