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Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Data Engineer to join our team and help shape a modern, scalable data platform. Youll work with cutting-edge AWS technologies, Spark, and Iceberg to build pipelines that keep our data reliable, discoverable, and ready for analytics.

Whats the Job?
Design and maintain scalable data pipelines on AWS (EMR, S3, Glue, Iceberg).
Transform raw, semi-structured data into analytics-ready datasets using Spark.
Automate schema management, validation, and quality checks.
Optimize performance and costs with smart partitioning, tuning, and monitoring.
Research and evaluate new technologies, proposing solutions that improve scalability and efficiency.
Plan and execute complex data projects with foresight and attention to long-term maintainability.
Collaborate with engineers, analysts, and stakeholders to deliver trusted data for reporting and dashboards.
Contribute to CI/CD practices, testing, and automation.
Requirements:
Requirements
Strong coding skills in Python (PySpark, pandas, boto3).
Experience with big data frameworks (Spark) and schema evolution.
Knowledge of lakehouse technologies (especially Apache Iceberg).
Familiarity with AWS services: EMR, S3, Glue, Athena.
Experience with orchestration tools like Airflow.
Solid understanding of CI/CD and version control (GitHub Actions).
Ability to research, evaluate, and plan ahead for new solutions and complex projects.

Nice to have:
Experience with MongoDB or other NoSQL databases.
Experience with stream processing (e.g., Kafka, Kinesis, Spark Structured Streaming).
Ability to create visualized dashboards and work with Looker (Enterprise).
Infrastructure-as-code (Terraform).
Strong debugging and troubleshooting skills for distributed systems.
This position is open to all candidates.
 
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04/02/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Senior Data Engineer in the Data Collection Ingest team to contribute to the design and coding of data ingestion services & pipelines. This role involves working as part of a team that handles millions of requests per minute across multiple servers, and is responsible for a wide-range of data pipelines, processing billions of events each day.
Why is this role so important?
As the most trusted platform for measuring online behavior, millions of people rely on insights daily as the ground truth for their knowledge of the digital world. Producing these insights requires large scale raw data to be ingested reliably in high scale to provide stable signals for analysis. As a Data Engineer you will have the opportunity to perform hands-on work and own raw data ingestion pipeline end-to-end. Your work will have a direct impact on the quality and reliability of our data and the insights that our products are delivering to our customers.
Requirements:
Has 5+ years of experience in developing code for big data infrastructure. Proficiency in technologies such as: Databricks, Spark, Airflow, Firehose, SQS, or other similar tools.
Proven experience working with high scale on AWS or any other cloud provider. Experience in architecture and design of large-scale and high performance production systems.
Comfortable taking challenges and learning new technologies.
Excellent communication skills with the ability to provide constant dialog between teams.
Ability to take business requirements and translate them to technical alternatives by performing risk management and evaluating tradeoffs.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
04/02/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Why is this role so important?
we are a data-focused company, and data is the heart of our business.
As a big data engineer developer, you will work at the very core of the company, designing and implementing complex high scale systems to retrieve and analyze data from millions of digital users.
Your role as a big data engineer will give you the opportunity to use the most cutting-edge technologies and best practices to solve complex technical problems while demonstrating technical leadership.
Requirements:
Passionate about data.
Holds a BSc degree in Computer Science\Engineering or a related technical field of study.
Has at least 5 years of software or data engineering development experience in one or more of the following programming languages: Python, Java, or Scala.
Has strong programming skills and knowledge of Data Structures, Design Patterns and Object Oriented Programming.
Has good understanding and experience of CI/CD practices and Git.
Excellent communication skills with the ability to provide constant dialog between and within data teams.
Can easily prioritize tasks and work independently and with others.
Conveys a strong sense of ownership over the products of the team.
Is comfortable working in a fast-paced dynamic environment.
Advantage:
Has experience with containerization technologies like Docker and Kubernetes.
Experience in designing and productization of complex big data pipelines.
Familiar with a cloud provider (AWS / Azure / GCP).
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
04/02/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Responsibilities
Design, implement, and maintain robust data pipelines and ETL/ELT processes on GCP (BigQuery, Dataflow, Pub/Sub, etc.).
Build, orchestrate, and monitor workflows using Apache Airflow / Cloud Composer.
Develop scalable data models to support analytics, reporting, and operational workloads.
Apply software engineering best practices to data engineering: modular design, code reuse, testing, and version control.
Manage GCP resources (BigQuery reservations, Cloud Composer/Airflow DAGs, Cloud Storage, Dataplex, IAM).
Optimize data storage, query performance, and cost through partitioning, clustering, caching, and monitoring.
Collaborate with DevOps/DataOps to ensure data infrastructure is secure, reliable, and compliant.
Partner with analysts and data scientists to understand requirements and translate them into efficient data solutions.
Mentor junior engineers, provide code reviews, and promote engineering best practices.
Act as a subject matter expert for GCP data engineering tools and services.
Define and enforce standards for metadata, cataloging, and data documentation.
Implement monitoring and alerting for pipeline health, data freshness, and data quality.
Requirements:
Requirements:
Bachelors or Masters degree in Computer Science, Engineering, or related field.
6+ years of professional experience in data engineering or similar roles, with 3+ years of hands-on work in a cloud env, preferably on GCP.
Strong proficiency with BigQuery, Dataflow (Apache Beam), Pub/Sub, and Cloud Composer (Airflow).
Expert-level Python development skills, including object-oriented programming (OOP), testing, and code optimization.
Strong data modeling skills (dimensional modeling, star/snowflake schemas, normalized/denormalized designs).
Solid SQL expertise and experience with data warehousing concepts.
Familiarity with CI/CD, Terraform/Infrastructure as Code, and modern data observability tools.
Exposure to AI tools and methodologies (i.e, Vertex AI).
Strong problem-solving and analytical skills.
Ability to communicate complex technical concepts to non-technical stakeholders.
Experience working in agile, cross-functional teams.

Preferred Skills (Nice to Have):
Experience with Google Cloud Platform (GCP) .
Experience with Dataplex for data cataloging and governance.
Knowledge of streaming technologies (Kafka, Confluent).
Experience with Looker.
Cloud certifications (Google Professional Data Engineer, Google Cloud Architect).
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
8531425
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דיווח על תוכן לא הולם או מפלה
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סגור
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
04/02/2026
Location: Jerusalem
Job Type: Full Time
We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives.
Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.
Your Arena
Design, develop, and maintain scalable, robust data pipelines and ETL processes
Architect and implement complex data models across various storage solutions
Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions
Ensure data quality, consistency, security, and compliance across all data systems
Play a key role in defining and implementing data strategies that drive business value
Contribute to the continuous improvement of our data architecture and processes
Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges
Participate in and sometimes lead code reviews to maintain high coding standards
Troubleshoot and resolve complex data-related issues in production environments
Evaluate and recommend new technologies and methodologies to improve our data infrastructure.
Requirements:
5+ years of experience in data engineering, with specific, strong proficiency in Python & software engineering principles - Must
Extensive experience with GraphDB - MUST
Extensive experience with AWS, GCP, Azure and cloud-native architectures - Must
Deep knowledge of both relational (e.g., PostgreSQL) and NoSQL databases - Must
Designing and implementing data warehouses and data lakes - Must
Strong understanding of data modeling techniques - Must
Expertise in data manipulation libraries (e.g., Pandas) and big data processing frameworks - Must
Experience with data validation tools such as Pydantic & Great Expectations - Must
Proficiency in writing and maintaining unit tests (e.g., Pytest) and integration tests - Must
Nice-to-Haves
Apache Iceberg - Experience building, managing and maintaining Iceberg lakehouse architecture with S3 storage and AWS Glue catalog - Strong Advantage
Apache Spark - Proficiency in optimizing Spark jobs, understanding partitioning strategies, and leveraging core framework capabilities for large-scale data processing - Strong Advantage
Modern data stack tools - DBT, DuckDB, Dagster or any other Data orchestration tool (e.g., Apache Airflow, Prefect) - Advantage
Designing and developing backend systems, including- RESTful API design and implementation, microservices architecture, event-driven systems, RabbitMQ, Apache Kafka - Advantage
Containerization technologies- Docker, Kubernetes, and IaC (e.g., Terraform) - Advantage
Stream processing technologies (e.g., Apache Kafka, Apache Flink) - Advantage
Understanding of compliance requirements (e.g., GDPR, CCPA) - Advantage
Experience mentoring junior engineers or leading small project teams
Excellent communication skills with the ability to explain complex technical concepts to various audiences
Demonstrated ability to work independently and lead technical initiatives
Relevant certifications in cloud platforms or data technologies.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
8531324
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
04/02/2026
Location: Jerusalem
Job Type: Full Time
We are seeking an experienced Senior Data Platform Engineer to design and scale the robust, cost-efficient infrastructure powering our groundbreaking fraud prevention solution. In this role, you will architect distributed systems and cloud-native technologies to safeguard our clients' revenue while driving technical initiatives that align with business objectives and operational efficiency.
Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.
Your Arena
Infrastructure & FinOps: Design scalable, robust backend services while owning cloud cost management to ensure maximum resource efficiency.
High-Performance Engineering: Architect distributed systems and real-time pipelines capable of processing millions of daily transactions.
Operational Excellence: Champion Infrastructure-as-Code (IaC), security, and observability best practices across the R&D organization.
Leadership: Lead technical initiatives, mentor engineers, and drive cross-functional collaboration to solve complex infrastructure challenges.
Requirements:
Experience: 5+ years of experience in data platform engineering, backend engineering, or infrastructure engineering.
Language Proficiency: Specific, strong proficiency in Python & software engineering principles.
Cloud Native: Extensive experience with AWS, GCP, or Azure and cloud-native architectures.
Databases: Deep knowledge of both relational (e.g., PostgreSQL) and NoSQL databases, including performance optimization, cost tuning, and scaling strategies.
Architecture: Strong experience designing and implementing RESTful APIs, microservices architecture, and event-driven systems.
Containerization & IaC: Experience with containerization technologies (Docker, Kubernetes) and Infrastructure-as-Code (e.g., Terraform, CloudFormation).
System Design: Strong understanding of distributed systems principles, concurrency, and scalability patterns.
Nice-to-Haves
Strong Advantage: Apache Iceberg (Lakehouse/S3/Glue), Apache Spark (Optimization), Message Queues (Kafka/Kinesis), Graph Databases (Experience with schema design, cluster setup, and ongoing management of engines like Amazon Neptune or Neo4j).
Tech Stack: Orchestration (Temporal/Dagster/Airflow), Modern Data Stack (dbt/DuckDB), Streaming (Flink/Kafka Streams), Observability (Datadog/Grafana).
Skills: FinOps (Cost Explorer/Spot instances), CI/CD & DevOps, Data Governance (GDPR), Pydantic, and Mentorship/Leadership experience.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8531320
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דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
03/02/2026
Job Type: Full Time
Welcome to Chargeflow Chargeflow is at the forefront of fintech + AI innovation, backed by leading venture capital firms. Our mission is to build a fraud-free global commerce ecosystem by leveraging the newest technology, freeing online businesses to focus on their core ideas and growth. We are building the future, and we need you to help shape it. Who We're Looking For - The Dream Maker We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives. Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud. Your Arena
* Design, develop, and maintain scalable, robust data pipelines and ETL processes
* Architect and implement complex data models across various storage solutions
* Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions
* Ensure data quality, consistency, security, and compliance across all data systems
* Play a key role in defining and implementing data strategies that drive business value
* Contribute to the continuous improvement of our data architecture and processes
* Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges
* Participate in and sometimes lead code reviews to maintain high coding standards
* Troubleshoot and resolve complex data-related issues in production environments
* Evaluate and recommend new technologies and methodologies to improve our data infrastructure
Requirements:
What It Takes - Must haves: 5+ years of experience in data engineering, with specific, strong proficiency in Python & software engineering principles - Must
* Extensive experience with GraphDB - MUST
* Extensive experience with AWS, GCP, Azure and cloud-native architectures - Must
* Deep knowledge of both relational (e.g., PostgreSQL) and NoSQL databases - Must
* Designing and implementing data warehouses and data lakes - Must
* Strong understanding of data modeling techniques - Must
* Expertise in data manipulation libraries (e.g., Pandas) and big data processing frameworks - Must
* Experience with data validation tools such as Pydantic & Great Expectations - Must
* Proficiency in writing and maintaining unit tests (e.g., Pytest) and integration tests - Must Nice-to-Haves
* Apache Iceberg - Experience building, managing and maintaining Iceberg lakehouse architecture with S3 storage and AWS Glue catalog - Strong Advantage
* Apache Spark - Proficiency in optimizing Spark jobs, understanding partitioning strategies, and leveraging core framework capabilities for large-scale data processing - Strong Advantage
* Modern data stack tools - DBT, DuckDB, Dagster or any other Data orchestration tool (e.g., Apache Airflow, Prefect) - Advantage
* Designing and developing backend systems, including- RESTful API design and implementation, microservices architecture, event-driven systems, RabbitMQ, Apache Kafka - Advantage
* Containerization technologies- Docker, Kubernetes, and IaC (e.g., Terraform) - Advantage
* Stream processing technologies (e.g., Apache Kafka, Apache Flink) - Advantage
* Understanding of compliance requirements (e.g., GDPR, CCPA) - A
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
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