לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER בתל אביב יפו, לחיפוש זה נמצאו 50 משרות

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 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.

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.

Required Senior Data Engineer
In your role as a Data Engineer, you'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.

We're looking for a Data Engineer to own and evolve the data infrastructure that sits underneath all of it. The pipeline is already built and running at real scale. Your job is to go deeper - embedding data further into the business and pushing the AI/ML layer forward. This isn't a maintenance role. It's an ownership role.

In this role, you will:

Our data pipelines run faster, scale cleaner, and break less - because you own the architecture and optimization of our BigQuery warehouse end-to-end.
High-throughput processing and real-time analytics become possible at a scale we haven't reached yet - because you're shaping the distributed systems that get us there.
Data capabilities land in the hands of the people who need them - data scientists, engineers, and product stakeholders from problem to solution, not as a downstream dependency.
The infrastructure gets more reliable, more automated, and easier to monitor - because you treat DevOps and MLOps as part of the job, not someone else's problem.
AI/ML models move from development into production and stay there - not handed off, but owned through the full deployment lifecycle.

we are looking for a Analytics Engineer.
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 are looking for a Data Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless workers who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance.

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.

Main responsibilities:
Provide the direction of our data architecture. Determine the right tools for the right jobs. We collaborate on the requirements and then you call the shots on what gets built.
Manage end-to-end execution of high-performance, large-scale data-driven projects, including design, implementation, and ongoing maintenance.
Optimize and monitor the team-related cloud costs.
Design and construct monitoring tools to ensure the efficiency and reliability of data processes.
Implement CI/CD for Data Workflows.

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

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.

Were on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the worlds first fully automated suite of vehicle inspection systems, with advanced AI at the core, spanning Machine Learning, GenAI, and computer vision across the automotive sector. With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, we stand at the forefront of automotive technological advancement. Our growing global team of over 300 employees is united around a culture of innovation, excellence, and teamwork as we build a safer automotive world.
We are looking for an experienced Research Scientist, Foundational Models to drive our long-term foundational model effort. You will design and train a single model that unifies all of our inspection segments (cars, trucks, fleets, tires, undercarriage, and future verticals) and serves as the basis for distillation into smaller, cheaper production models.
A day in the life and how youll make an impact
* Design and run large-scale pretraining experiments over our multi-segment inspection data.
* Develop self-supervised and multi-task learning recipes that transfer cleanly across vehicle segments and use cases.
* Build distillation pipelines that hand off compact, efficient models to production teams.
* Drive fast-adaptation methods so new segments and customers can be onboarded with minimal labels.
* Set and uphold ourresearch bar through rigorous evaluation, ablations, and publication-quality work.

We are seeking a skilled and motivated Data Engineer with expertise in Elasticsearch, cloud technologies, and Kafka. As a data engineer, you will be responsible for designing, building and maintaining scalable and efficient data pipelines that will support our organization's data processing needs.
The role will entail:
Design and develop data platforms based on Elasticsearch, Databricks, and Kafka
Build and maintain data pipelines that are efficient, reliable and scalable
Collaborate with cross-functional teams to identify data requirements and design solutions that meet those requirements
Write efficient and optimized code that can handle large volumes of data
Implement data quality checks to ensure accuracy and completeness of the data
Troubleshoot and resolve data pipeline issues in a timely manner.

Required Software & Data Engineer
Tel Aviv
We are on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Software & Data Engineer, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how we understand and improve our service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how we operate
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.