לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER בתל אביב יפו, לחיפוש זה נמצאו 63 משרות

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across all of our company.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build our company's next-generation data stack.
We believe three things matter for every role at our company: 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 you'll
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals.

Appdome's mission is to protect every mobile app in the world and the people who use them. We are the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps — with no SDKs, no coding, and no disruption to engineering cycles.
Our platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities, powered by deep learning models trained on a decade of mobile defense data and trillions of live threat events. From build time to runtime, Appdome's AI Agents help mobile brands detect, investigate, and respond to threats faster than ever — recognized as the best AI Platform for Cyber Resilience at RSA Conference 2026 for the second consecutive year. Leading financial, healthcare, m-commerce, and B2B brands rely on Appdome to secure over 50,000 mobile apps and protect more than 1 billion end users globally.
Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.
?About the Role
We are looking for a Data Assurance Engineer with strong experience in data validation, automation, analytics testing, and large-scale event pipeline quality.
This role is focused on ensuring the accuracy, stability, and reliability of data across our analytics and security event systems. The ideal candidate will be responsible for building automated validations, investigating data discrepancies, monitoring data quality, and working closely with engineering, data, and product teams.
Responsibilities

* Design, build, and maintain automated validation processes for large-scale event pipelines.
* Validate end-to-end data flows across ingestion, processing, storage, and dashboard layers.
* Create SQL-based validations to verify event counts, unique devices, metadata accuracy, schema
* consistency, latency, and data freshness.
* Investigate discrepancies between production systems, staging environments, data warehouses, object
* storage, and customer-facing dashboards.
* Monitor event volume, data latency, anomalies, spikes, drops, duplicates, and missing data.
* Build and maintain CI/CD validation jobs using tools such as Jenkins or GitLab CI.
* Create clear automated reports, dashboards, and email summaries for validation results.
* Work closely with backend engineers, data engineers, QA teams, and product stakeholders to identify,
* report, and validate fixes for data quality issues.
* Support performance and scalability testing for analytics dashboards, queries, and data pipelines.
* Help improve internal data assurance processes, data observability, and production monitoring.

we are looking for a Senior Data Engineer.
ou'll be actively engaged in the most fascinating and demanding projects for our clients. Handling high-scale operations, heavy traffic, stringent SLAs, and massive data volumes is just the starting point. Our leadership in the realms of Big Data, Streaming Data, and Complex Event Processing (CEP) stems from our adept use of cutting-edge, optimal technologies.
Responsibilities:
Apply software-engineering methods and best practices (Medallion Architecture) in Data Lake management, using tools like DBT.
Develop Data pipelines to ingest and transform data.
Manage and enhance orchestrated pipelines across company
Data Modeling: Developing data models to ensure efficient storage, retrieval, and processing of data, often involving schema design for NoSQL databases, data lakes, and data warehouses. This will also include catalogs of data.
Scalability: Ensuring that the big data architecture can scale horizontally to handle large volumes of data and high traffic loads.
Data Security: Implementing security measures to protect sensitive data, including encryption, access controls, and data masking.
Data Governance: Establishing data governance policies to ensure data quality, compliance with regulations, and data lineage.

the leading global financial news & data platform, is on the lookout for a Senior Data Engineer to join our growing data team!
In this role, you will design and develop scalable data solutions, optimize data workflows, and support critical business processes. You will work with a variety of databases and big data tools in a cloud environment, focusing on data modeling, governance, and analytics.
What youll be doing:
Design, develop, and maintain end-to-end ETL pipelines, from gathering business requirements to implementation.
Work with multiple database technologies, especially BigQuery.
Optimize data models (DWH, fact & dimension tables, RI, SCDs) for performance and scalability.
Implement data governance best practices and maintain comprehensive documentation.
Utilize Big Data tools in cloud environments (GCP preferred).
Develop and support complex business workflows and data processes.
Design and implement monitoring systems to ensure data quality throughout the pipeline.
Workflow orchestration using Apache Airflow.
Collaborate with analysts and stakeholders to ensure high-quality data for business insights.
Support and optimize Tableau infrastructure for data visualization.

We are building next-generation SaaS 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 data pipeline (Python) 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 in a GCP cloud environment.
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 Malware Protection.

we are looking for a Research Infra Engineer.
As a Research Infra Engineer, you will build and operate the shared platforms that power 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 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're seeking a Mid to Senior Data Engineer to join our Cloud Identity & Perimeter, a critical component of CrowdStrike's 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 position is based in our Tel Aviv, Israel office and requires strong leadership presence and ability to work closely with cross-functional teams.

we are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platform-supporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do:
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.

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

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.

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

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

We are looking for an Experienced Backend Engineer to join our Data Foundations team.

What Youll Do:
Dive into the heart of engineering core as a pivotal member of our team, dedicated to constructing the internal tools and services that are the cornerstone of our data-centric universe. Your role is at the intersection of innovation and collaboration, focusing on creating sophisticated solutions that streamline data versioning, enhance data processes, and facilitate seamless interactions across all data teams. In this team, you will be building the robust framework that enables all other teams to manage and leverage data with unprecedented efficiency and accuracy. Your contributions will not only improve our internal workflows but also amplify the impact of our data on client success.

We are looking for a Data Engineering Team Lead to drive the development and optimization of our data infrastructure.


So, what will you be doing all day?
Team Management

Serve as the direct manager for data engineers, providing regular feedback, career guidance, and technical mentorship.
Translate business requirements into actionable technical roadmaps; prioritize and assign daily tasks using sprint methodologies.
Cultivate a collaborative, high-performance team culture focused on continuous improvement and engineering excellence.
Cultivate a collaborative, high-performance team culture rooted in a delivery mindset, a business-driven focus, and engineering excellence.


Hands on Engineering

Design, build, and maintain robust, scalable data pipelines capable of processing massive datasets.
Oversee and maintain multiple development and production environments to ensure seamless deployment and high availability.
Design and implement highly cost-efficient cloud data infrastructure, constantly monitoring and optimizing resource utilization.
Research, develop, and integrate AI models and autonomous agents into the data ecosystem to automate pipeline monitoring, optimize data curation, and unlock intelligent data-driven capabilities.

Were looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D.

So, what will you be doing all day?

Your role as part of the R&D team means your daily responsibilities may include:

Design and implement complex high scale systems using a large variety of technologies.
You will work in a data research team alongside other data engineers, data scientists and data analysts. Together you will tackle complex data challenges and bring new solutions and algorithms to production.
Contribute and improve the existing infrastructure of code and data pipelines, constantly exploring new technologies and eliminating bottlenecks.
You will experiment with various technologies in the domain of Machine Learning and big data processing.
You will work on a monitoring infrastructure for our data pipelines to ensure smooth and reliable data ingestion and calculation.