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

we are looking for a Data Engineer.
As a Data Engineer, you will provide data-driven decision making support for ' merchants. You will deliver an improved understanding of the merchants metrics and improve service and customer satisfaction.
Youll work closely with various teams, including Analytics & Research, Finance, Account Management, and Product Management.
What You'll Be Doing:
Work with various teams to define key metrics (KPIs) and provide the methodologies to accurately measure performance
Create new ETL processes and optimize existing ones
Create smart, innovative and effective visualization methods, and promote engagement and implementation of them

Were looking for a Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Data Science Team Manager in the R&D.
So, what will you be doing all day?
Building and maintaining our big-data pipelines
Take a major part in designing and implementing complex high-scale systems using a large variety of technologies
Be part of a team with smart and motivated engineers, and data scientists, to collaborate on the planning, development, and maintenance of our products
Implement solutions in the AWS cloud environment, and work in Databricks with PySpark

we are looking for a Senior Analytics Engineer.
On a day-to-day basis, we transform raw data into clean, structured models using tools like SQL, Python, and dbt. We build and maintain modern BI platforms, develop reporting systems, and design AI-driven analytics that surface valuable insights quickly and reliably.
Our team is hands-on with building reusable metrics, defining source-of-truth data models, and ensuring consistency through a strong semantic layer. Whether were shipping a new dashboard, debugging a dbt model, or refining how a metric is defined across the business, our focus is always on clarity, scalability, and enabling smarter, faster decisions.

We are looking for a Backend Engineer to join our MLOps team and help build the infrastructure that powers cutting-edge AI models.
In this role, youll manage the end-to-end MLOps lifecycle, designing event-driven systems that handle massive video data and moving compute-intensive, generative models from research to production.
You'll collaborate closely with AI researchers and video-processing teams to ensure our AI services are scalable, reliable, and performant.

We are looking for a strong, hands-on Data Engineer to join our team and play a key role in building our data infrastructure from the ground up. In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases. You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption. This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.
What will your job look like?
Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
Design and implement scalable, flexible data architectures to support evolving business needs.
Build and manage data platforms, including data lakes and data warehouses.
Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.

We're hiring a Data Engineer to join our growing team of analytics experts in order to help & lead the build-out of our data integration and pipeline processes, tools and platform.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The right candidate must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our companys data architecture to support our next generation of products and data initiatives.
In this role, you will be responsible for:
Create ELT/Streaming processes and SQL queries to bring data to/from the data warehouse and other data sources.
Establish scalable, efficient, automated processes for large-scale data analyses.
Support the development of performance dashboards & data sets that will generate the right insight.
Work with business owners and partners to build data sets that answer their specific business questions.
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization.
Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
Own the data lake pipelines, maintenance, improvements and schema.

We are looking for a Staff Data Platform Engineer to join our Engineering team and lead the evolution of our next-generation data platform. In this high-impact role, you will operate as a player-coach: you will be the technical visionary responsible for designing the ecosystem, while remaining deeply hands-on to implement scalable, secure, and intelligent solutions that power everything from operational reporting to advanced GenAI applications.
You will bridge the gap between complex business requirements and technical execution, advocating for a data-first culture. This role offers a clear growth path: while it currently starts as an individual contributor position, it has the potential to evolve into a leadership role.
About the Role:
Architecture & Hands-on Execution: Design and actively build a comprehensive data platform. You will not just oversee infrastructure; you will write the core code and build tools that support diverse workloads-from operational reporting to complex analytical queries.
Strategic & Technical Delivery: Partner with product managers to translate business objectives into technical strategies, then lead the engineering effort to deliver them.
Technology Evaluation: Continuously evaluate, prototype, and select best-in-class technologies to future-proof our data stack.
Technical Leadership & Mentorship: Act as a primary advocate for platform adoption. You will foster a community of practice around data engineering, mentoring senior and mid-level engineers to elevate the team's technical bar.
Governance & Quality: Implement and automate robust frameworks for Data Discovery, Quality, and Governance, ensuring solutions are trustworthy and compliant with financial regulations.

We seek an experienced and highly skilled Senior Engineer to join our Data Platform Team. This is an exciting opportunity to work on cutting-edge technologies, drive innovation, and play a key role in designing and implementing the companys data infrastructure and architecture.

What you'll do

Database Infrastructure Development - Design, develop, and maintain scalable and reliable self-serve database infrastructure, including PostgreSQL, MongoDB, SingleStore, and AWS Aurora.

Big Data Infrastructure Development - Design, develop, and maintain scalable and reliable self-serve big data infrastructure, including cloud-agnostic data lakehouse, distributed databases, and platform-powered data pipelines.

End-to-End Ownership - Take responsibility for the entire lifecycle of data infrastructure, from DevOps (Terraform, Kubernetes) to application-level components (infrastructure libraries, core components in data pipelines).

Architecture Leadership: Collaborate with the Architecture group to define and maintain the companys core architectural vision.

Partner with development teams, providing technical guidance, best practices, and support from the design phase to production deployment.

Innovation and Exploration - Work on diverse and impactful projects across different layers of the tech stack, exploring new technologies and approaches to improve reliability, efficiency, and scalability.

one of the world's most impactful shopping recommendation companies, is searching for a talented Data Engineer to join our innovative team. For the past decade, we've served tens of millions of users globally, and we're looking for a passionate individual to help us continue our journey of making an impact.
What You'll Own:
Data Infrastructure
Build and operate data pipelines on GCP using Cloud Workflows, Cloud Functions, Cloud Scheduler, and BigQuery.
Create, Transform and Manage Datasets (Python, DBT,..)
Design and implement API integrations to pull data from affiliate networks, ad platforms, and internal services.
Ensure pipeline reliability, observability (monitoring, alerting, SLA management), and scalability.
Data Quality & Trust
Implement tests, freshness checks, and anomaly detection across all critical models.
Lead incident triage and root-cause analysis when data issues arise; build systems that catch problems before stakeholders do.
Maintain clear documentation of data contracts, schema definitions, and transformation logic.
ML & Data Science Collaboration
Work hand-in-hand with Data Scientists building ML models - ensuring feature tables, training datasets, and inference pipelines are clean and reproducible.
Build the data layer that feeds ML model training and evaluation, including feature stores and labeled datasets.

we are looking for a Senior Data Engineer I.
As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.
21679

we are looking for a Data Engineer.
As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and ore.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.
20718

As an Analytics Engineer within the Delivery & Operations organization, you will operate at the intersection of data engineering and analytics, with a strong focus on data quality, reliability, and scalability.

This role combines hands-on ownership of data pipelines and data transformations with the ability to effectively interface with customer-facing teams (Customer Success, and Delivery) when needed-helping ensure that data outputs are accurate, clear, and aligned with real-world use cases.

Responsibilities:
Build and maintain data models, pipelines, and ETL processes to support analytics, reporting, and machine learning.
Own data quality and validation, including monitoring, auditing datasets, and identifying anomalies.
Support customer-facing teams by providing reliable data, clarifying definitions, and investigating data issues.
Collaborate cross-functionally and work with existing codebases to debug, improve, and maintain data workflows.
Ensure high-quality data across the lifecycle to support reliable ML pipelines.

We're seeking a Mid to Senior Data Engineer to join our Cloud Identity & Perimeter, a critical component of our 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 searching for a Senior Data Engineer to join our growing team in Tel Aviv and serve as a cornerstone of data evolution. We need an experienced, high-impact engineer ready to elevate our infrastructure from "functional" to "world-class."

As a pivotal member of the team, you wont just build pipelines; you will architect the future of our data ecosystem. Were looking for someone who obsesses over query latency, high-performance analytics, and cost-efficiency - someone who views data integrity as non-negotiable and thrives on turning complex event streams into elegant, scalable models.

Responsibilities
Lead the end-to-end data strategy, evolving our event-driven architecture to ensure seamless, low-latency data flow across the organization.
Design and implement robust, scalable data models that serve as the "single source of truth" for the entire organization.
Act as our internal Snowflake expert - optimizing performance and cost through best practices in clustering, materialized views, and warehouse management.
Build and maintain sophisticated ELT/ETL pipelines that transform raw event data into actionable insights, with a heavy focus on reliability and observability.
Proactively identify infrastructure bottlenecks and re-engineer processes to handle increasing scale without breaking a sweat.
Partner closely with Product and Engineering teams to translate business needs into technical reality, while mentoring analysts and peers on high-quality SQL and architectural standards.

Were looking for a talented Data Engineer to join our Data team and spread the power of our company. The Data team develops and maintains the infrastructure for internal data and product analytics. We are looking for data enthusiasts, independent, logical thinkers with a can-do approach and a passion for problem-solving. We run a SaaS-based stack using BigQuery, Snowflake and dbt.
WHAT YOU'LL DO
Design, build, and maintain data pipelines, datasets and catalogs for fast-growing products and business groups.
Develop self-service data analytics solutions and infrastructure.
Support ad hoc needs and requests of internal stakeholders.
Collaborate with analysts, engineers, and internal customers from Product, Finance, Revenue, and Marketing.