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.
As a Senior Data Engineer, you will collaborate closely with engineering teams, product managers, and stakeholders across the organization. You will not only build the infrastructure utilizing modern data stack tools but also act as a data analyst when needed, ensuring our systems are fully equipped to operate within and support a cutting-edge agentic AI environment.
Responsibilities
Design, build, and maintain highly scalable ELT/ETL data pipelines.
Architect and manage modern cloud data warehousing solutions.
Develop, maintain, and monitor Python services responsible for robust data collection and ingestion.
Perform hands-on data analysis to interpret complex datasets, identify trends, and deliver business insights, acting in a dual capacity as a Data Analyst.
Develop and optimize data infrastructure specifically designed to support autonomous agentic workflows and LLM integrations.
Collaborate with engineers and analysts to troubleshoot data issues, enforce quality SLAs, and define data requirements.
Document data architecture, flow, and analytics standards for internal team alignment.
Build and maintain dashboards and reports to communicate analytical findings and data health to the organization.
Maintain Kafka consumer applications that process high-volume event streams in real-time, ensuring reliable ingestion into cloud databases.
Must-Have:
5+ years of proven experience in a Data Engineering role, with a strong background in data architecture.
Exceptional proficiency in SQL and Python for data manipulation, scripting, and pipeline automation.
Deep hands-on experience with modern data orchestration and transformation tools, specifically Airflow and dbt.
Extensive experience managing and optimizing cloud data platforms such as BigQuery / Databricks / Snowflake.
Demonstrated experience in data analysis, with the ability to act as a Data Analyst to query data, build reports, and extract actionable insights.
Practical experience designing or supporting data infrastructure for an agentic environment or AI/LLM-driven applications.
Strong attention to detail, analytical mindset, and excellent communication skills.
Experience of one or more of these technologies: Kafka, Kubernetes, ArgoCD, Terraform, Debezium.
Understanding of data modeling principles: dimensional modeling, fact/dimension tables, slowly changing dimensions
Experience with Git workflows: branching, PRs, code reviews, and CI/CD for data pipelines.
Ownership mindset: ability to debug production issues, drive projects to completion independently
Nice-to-Have:
Experience with BI tools (e.g., Looker, Tableau, Power BI) for advanced dashboarding.
Experience working with graph databases or NoSQL databases.
Experience with Python backend APIs (FastAPI/Flask) that serve aggregated analytics data to dashboards.
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.
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