לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER

We seek a skilled Senior Infra Backend Engineer to join our R&D office in Tel Aviv, working in a hybrid and flexible model.
Youll collaborate with a top-tier R&D team and take your professional growth to the next level. Our backend infra teams work mainly with Python and Go, but we welcome talented backend engineers from any language background.

Example Projects

Researching and running POCs of new technologies to select the optimal solution for system requirements.

Migrating massive amounts of user-level data into Iceberg, while keeping scale and cost efficiency in mind.

Designing and implementing a robust pipeline capable of ingesting billions of real-time events daily (hundreds of thousands per second).

Exploring and choosing database and streaming technologies to support a rapidly growing clientele base.

Leading the design and development of a new streaming ETL product with low memory footprint and efficient processing.


Key Responsibilities

Design and build scalable pipelines processing billions of events daily.

Dive deep into infra technologies and optimize them at scale.

Lead major efforts from idea initiation → design → implementation.

Tackle complex challenges in scalable architecture within our AWS environment.

Integrate and leverage top industry technologies such as Kafka, Iceberg, DynamoDB, Postgres, EMR, Kubernetes, Druid, Snowflake, and more.

A fast-growing fintech AI start-up company, focused on eliminating fraud and chargebacks in online commerce, is looking for an experienced Senior Data Engineer.
In this Roll, you will build large-scale, cutting-edge data solutions for fraud prevention, with the potential to grow into a technical leadership role.
The company is located in Modi'in, central Israel. Hybrid work model.
Responsibilities
Build and maintain scalable data pipelines and ETL processes.
Design complex data models and optimize data architecture.
Collaborate with teams to deliver high-quality, compliant solutions.
Troubleshoot production issues and implement best practices.
Recommend new technologies to enhance the data infrastructure.

Were looking for an experienced Data Engineer to join our DEX Platform and help drive the next stage of our growth. In this role, youll design, build, and scale data infrastructure and advanced processing pipelines that power real-time insights and intelligent automation across our platform.
As a senior data engineer, youll own the full service lifecycle-from architecture and development to deployment, monitoring, and scaling-while ensuring data quality, reliability, and compliance. Youll work closely with backend, AI, and data teams to deliver robust, production-ready systems that support our AI-first strategy and our mission to make the workplace run itself.

we are looking for a Data Engineer.
This is a full-time, on-site role for a Data Engineer at WideOps Ltd., located in Haifa.
The Data Engineer will design, build, and maintain scalable data pipelines, implement robust Extract, Transform, Load (ETL) processes, and develop efficient data models to support business intelligence and data analytics needs.
The role also involves building and improving data warehousing solutions and collaborating with cross-functional teams to ensure data integrity and optimize workflows.

We are seeking a skilled and motivated Data Engineer to join our dynamic team. The ideal candidate will have extensive experience in building and optimizing data pipelines, handling large datasets, and working within cloud-based and on-premise environments.
You will be responsible for designing and implementing efficient, scalable solutions to manage, process, and analyze high volumes of data, ensuring the reliability and performance of our data infrastructure.
What will your job look like:
Design, build, and maintain scalable data pipelines to process large datasets efficiently
Develop and implement data models and architectures that support both real-time and batch data processing
Ensure data integrity, security, and accuracy across all systems
Collaborate with data scientists, analysts, and other engineers to ensure data availability and quality
Optimize data retrieval and storage processes to handle large volumes of data seamlessly
Work with structured, semi-structured, and unstructured data, integrating various data sources
Troubleshoot and resolve data issues, ensuring continuous operation of the data infrastructure
Maintain and enhance ETL processes, ensuring scalability and performance in handling large datasets
Stay up-to-date with industry best practices and emerging technologies related to big data engineering

We are looking for a Data Engineer to join our Object Detection group and play a key role in managing and enabling data workflows that power our computer vision algorithms. Our team generates and processes large volumes of diverse data from multiple sources, and we need someone who can bridge the gap between raw data and algorithmic innovation.
Working alongside algorithm developers and researchers, you'll be responsible for building robust data pipelines, ensuring data quality, and making complex datasets accessible and actionable for our detection models.
This role requires both strong coding abilities and a deep understanding of data - you'll need to think like an engineer while understanding the unique needs of a research and development-focused algorithmic group.
What will your job look like:
Work on large-scale systems handling diverse data from multiple sources
Build and maintain robust data pipelines that enable algorithmic development
Evaluate various optional technologies and take part in decision-making
Own key features and services within the data infrastructure
Ensure data quality and accessibility for detection models and research needs
Work onsite in Jerusalem at least 3 days a week

Were looking for a talented Data Engineer to join our Data team and spread our power. 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.

Were looking for a Senior Data Engineer to lead the architecture and development of large-scale, production-grade data pipelines supporting ML inference systems.
What will your job look like:
Architect and own end-to-end data pipelines for large-scale model inference
Design high-throughput, scalable data streaming to the cloud
Integrate data conversion into data collection and inference pipelines
Drive performance, scalability, and reliability across distributed systems
Partner with ML, platform, and infrastructure teams

We are looking for a Principal Data Engineer to join our Engineering team. This is a hybrid role based in Israel, reporting to the Senior Manager, Software Development Engineering. You will play a key role in designing, building, and maintaining the data pipelines that fuel business insights for the worlds largest cloud security platform. You will bring vision and passion to a team of experts enabling organizations worldwide to harness speed and agility through a cloud-first strategy.
What youll do (Role Expectations):
Design, develop, and implement scalable resilient data pipelines using Apache Spark, Databricks, and Delta Lake
Lead projects end-to-end through implementation, testing, deployment, and monitoring while collaborating with engineering teams across the organization
Research and investigate new SaaS platforms and APIs to uncover opportunities for new security detections
Optimize data infrastructure to ensure smooth operation, performance efficiency, and data integrity throughout the data lifecycle
Act as a force multiplier by mentoring senior engineers and setting high technical standards across the team.

were looking for skilled professionals to help shape our data platform and drive the next generation of trading technology.

In this role you will:
Design, implement, and maintain scalable data pipelines using Python and orchestration tools like Apache Airflow.

Take a leading role in evaluating and selecting foundational components of our data stack (e.g., Databricks vs. Snowflake).

Architect and optimize data workflows across AWS and on-premise environments.

Work with modern file formats (Iceberg, Parquet, ORC) and understand their trade-offs for performance, cost, and scalability.

Collaborate with analysts, engineers, and stakeholders to provide accessible and reliable datasets.

Help assess and implement frameworks such as DBT for data transformation and modeling.

Develop best practices and internal standards for data engineering, monitoring, and testing.

Contribute to the long-term vision and roadmap of Fin-on-exs data infrastructure.

we are Crafting Tomorrow's Retail Experience
We started with a simple question: How can vision AI make shopping better for everyone? Today, our team of passionate experts is transforming how people shop and how retailers operate, one store at a time.
Our goal is to solve real retail challenges by developing advanced computer vision AI that prevents loss, enables grab-and-go shopping, and turns store data into valuable insights, all while delivering clear value from day one.
With multiple global deployments, deep partnerships with leading retailers, and a product suite thats proving its impact every day, our company isnt just imagining the future of retail, were building it.
We are looking for a Data Engineer to join our Customer Performance team and help shape the foundation of our companys data platform.
You will own the data layer, evolve our BI semantic layer on a modern BI platform, and enable teams across the company to access and trust their data. Working closely with analysts and stakeholders in Operations, Product, R&D, and Customer Success, youll turn complex data into insights that drive performance and customer value.
A day in the life
Build and expand our companys analytics data stack
Design and maintain curated data models that power self-service analytics and dashboards
Develop and own the BI semantic layer on a modern BI platform
Collaborate with analysts to define core metrics, KPIs, and shared business logic
Partner with Operations, R&D, Product, and Customer Success teams to translate business questions into scalable data solutions
Ensure data quality, observability, and documentation across datasets and pipelines
Support complex investigations and ad-hoc analyses that drive customer and operational excellence.

Our team is responsible for the data and data infrastructure that processes billions of records daily, driving critical business insights for both internal and external customers across the organization.
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 diverse infra and multi-stage pipelines with intricate data structures and advanced queries, and complex BI.
A bit about our infrastructure. Our main databases are Snowflake, Iceberg on AWS, and Trino. Spark on EMR processes the huge influx of data. Airflow does most of the ETL.
The data we deliver drives insights both for internal and external customers. Our internal customers use it routinely for decision-making across the organization, such enhancing our product offerings.
What Youll Do
Build, maintain, and optimize data infrastructure.
Contribute to the evolution of our AWS-based infrastructure.
Work with database technologies - Snowflake, Iceberg, Trino, Athena, and Glue.
Utilize Airflow, Spark, Kubernetes, ArgoCD and AWS.
Provide AI tools to ease data access for our customers.
Integrate external tools such as for anomaly detection or data sources ingestion.
Use AI to accelerate your development.
Assures the quality of the infra by employed QA automation methods.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

Your Mission As a Senior Data Engineer, your mission is to build the scalable, reliable data foundation that empowers us to make data-driven decisions. You will serve as a bridge between complex business needs and technical implementation, translating raw data into high-value assets. You will own the entire data lifecycle-from ingestion to insight-ensuring that our analytics infrastructure scales as fast as our business.

Key Responsibilities:
Strategic Data Modeling: Translate complex business requirements into efficient, scalable data models and schemas. You will design the logic that turns raw events into actionable business intelligence.
Pipeline Architecture: Design, implement, and maintain resilient data pipelines that serve multiple business domains. You will ensure data flows reliably, securely, and with low latency across our ecosystem.
End-to-End Ownership: Own the data development lifecycle completely-from architectural design and testing to deployment, maintenance, and observability.
Cross-Functional Partnership: Partner closely with Data Analysts, Data Scientists, and Software Engineers to deliver end-to-end data solutions.