עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!

במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.

מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.

חברה בתחום כללי

תל אביב - יפו

חברה בתחום כללי

תל אביב - יפו
מלאה
25,000-35,000 ₪ הערכה מבוססת AI ולא שכר שהתקבל מהמעסיק
זוהי הערכת טווח שכר מבוססת AI ולא שכר שהתקבל מהמעסיק

We are looking for engineers with proven experience working with large-scale datasets and distributed systems, who are passionate about data quality, performance, and system reliability.

Responsibilities:

Design and implement scalable, fault-tolerant ETL pipelines using Apache Spark for high-throughput, real-time and batch data processing.
Develop and manage CI/CD pipelines, testing strategies, and data quality frameworks to ensure robust data workflows.
Collaborate with data scientists, analysts, and product teams to build data models, maintain data lineage, and surface insights that drive business value.
Evaluate and integrate new technologies to enhance performance, scalability, and cost-efficiency in our data ecosystem.
Own and evolve critical components of our data infrastructure, with a deep understanding of both technical architecture and business context.

Requirements:
6+ years of hands-on experience as a Data Engineer or Backend Engineer, with a strong focus on data-intensive systems.
Mandatory: Proven, production-grade experience with Apache Spark at scale (tens of terabytes daily or more).
3+ years of experience python.
Experience with cloud-native architectures, especially AWS (e.g., S3, EMR, Athena, Glue).
Expertise in designing and maintaining ETL pipelines using orchestration tools like Airflow (or similar).
Strong analytical skills and proficiency in SQL.
Experience working in distributed environments and optimizing performance for large-scale data workloads.
Ability to lead initiatives and work independently in a fast-paced environment.

This position is open to all candidates.