Data Engineer

Job description

Fundbox is looking for a talented Data Engineer to join our exceptional Data Engineering team.

As a data engineer at Fundbox, you will design, build, and optimize robust data pipelines, integrating diverse data sources into our analytics platform. With a focus on cloud infrastructure, collaborate closely with cloud-based services to architect and manage a scalable data infrastructure, facilitating collaboration across cross-functional teams for effective solution delivery.

Join us in implementing the financial future of Small and Medium Businesses using cutting-edge technologies.

Responsibilities

• Data Pipeline: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate data from various sources into our analytics platform.
• Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform.
• Cloud Infrastructure: Work closely with cloud-based services, to design and manage a scalable data infrastructure.
• Collaboration: Interact with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs.
• Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security.
• Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure.

Requirements

• Degree: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• Experience: A minimum of 3 years as a Data Engineer and 6+ years of professional experience in software development.
• Spark expertise: Deep knowledge of Apache Spark, as well as hands-on experience building data processing applications using Spark’s core libraries.
• Data Engineering: Experience designing and implementing ETL pipelines, data integration, and data transformation processes.
• Cloud Platforms: Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
• Streaming technologies like Kafka, Flink, or Kinesis.
• ETL Tools and Orchestration: Familiarity with ETL tools and frameworks, such as Apache Airflow.
• Collaboration and Communication: Effective communication skills and collaboration within cross-functional teams.

Tel Aviv Office

Our Tel Aviv office is located in the heart of the city, right off Rothschild Boulevard. It has 360 degree views and is a few steps from amazing bars and restaurants.