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 הייטק / חומרה / תוכנה / סייבר

תל אביב - יפו

חברה בתחום הייטק / חומרה / תוכנה / סייבר

תל אביב - יפו
מלאה
28,000-40,000 ₪ הערכה מבוססת AI ולא שכר שהתקבל מהמעסיק
הערכה מבוססת AI ולא שכר של המעסיק

We are looking for a Data Engineer to join our team and play a key role in designing, building, and maintaining scalable, cloud-based data pipelines. You will work with AWS (Redshift, S3, Glue, Managed Airflow, Lambda) to integrate, process, and analyze large datasets, ensuring data reliability and efficiency.

Your work will directly impact business intelligence, analytics, and data-driven decision-making across the

What Youll Do:
ETL & Data Processing: Develop and maintain ETL processes, integrating data from various sources (APIs, databases, external platforms) using Python, SQL, and cloud technologies.
Cloud & Big Data Technologies: Implement solutions using PySpark, Databricks, Airflow, and cloud platforms (AWS) to process large-scale datasets efficiently.
Data Modeling: Design and maintain logical and physical data models to support business needs.
Optimization & Scalability: Improve process efficiency and optimize runtime performance to handle large-scale data workloads.
Collaboration: Work closely with BI analysts and business stakeholders to define data requirements and functional specifications.
Monitoring & Troubleshooting: Ensure data integrity and reliability by proactively monitoring pipelines and resolving issues.
Data Modeling: Design and maintain logical and physical data models to support analytics and operational needs

Requirements:
BSc in Computer Science, Engineering, or equivalent practical experience.
3+ years of experience in data engineering or related roles.
Technical Expertise:
Proficiency in Python for data engineering and automation.
Experience with Big Data technologies such as Spark, Databricks, DBT, and Airflow.
Hands-on experience with AWS services (S3, Redshift, Glue, Managed Airflow, Lambda)
Knowledge of Docker, Terraform, Kubernetes, and infrastructure automation.
Strong understanding of data warehouse (DWH) methodologies and best practices.
Soft Skills:
Strong problem-solving abilities and a proactive approach to learning new technologies.
Excellent communication and collaboration skills, with the ability to work independently and in a team.

This position is open to all candidates.