Senior Backend Infrastructure Specialist

1 day ago

Tel Aviv, Tel Aviv, Israel beBeeDataEngineer Full time
Job Overview

We're building the future of mobility today. Our mission is to optimize existing operations and seamlessly launch new business models for the world's largest vehicle fleet operators and transportation providers.

At the heart of our platform lies data infrastructure, driving advanced machine learning models and optimization algorithms. As a Senior Data Engineer, you'll be responsible for owning and scaling the backend data infrastructure that powers our platform—supporting real-time optimization, advanced analytics, and machine learning applications.

Key Responsibilities

  • Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
  • Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
  • Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
  • Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
  • Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
  • Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.

Requirements

  • 4+ years in backend data engineering or infrastructure-focused software development.
  • Proficient in Python, with experience building production-grade data services.
  • Solid understanding of SQL 
  • Proven track record designing and operating scalable, low-latency data pipelines (batch and streaming).
  • Experience building and maintaining data platforms, including lakes, pipelines, and developer tooling.
  • Familiar with orchestration tools like Airflow, and modern CI/CD practices.
  • Comfortable working in cloud-native environments (AWS, GCP), including containerization (e.g., Docker, Kubernetes).

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