לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER בראש העין, לחיפוש זה נמצאו 4 משרות

We are looking for a talented and experienced Mid-Level Data Engineer with a passion for data and cloud technologies to join our team. In this role, you will be a key player in designing, developing, and maintaining our AWS and Databricks-based data platform. You will bridge the gap between robust Data Engineering, Database Administration (DBA), and high-performance Analytics Engineering.

The ideal candidate understands the Lakehouse architecture, has experience managing modern cloud data warehouses like Snowflake, and possesses the ability to build scalable ETL pipelines that drive data-driven business decisions.

Key Responsibilities

End-to-End Pipelines: Develop and maintain complex ETL/ELT pipelines using Python/PySpark on the Databricks platform, as well as loading and transforming data within Snowflake.
Data Architecture: Implement and manage data layers following the Medallion architecture (Bronze, Silver, Gold) using Delta Lake.
Optimization & Analytics: Set up and manage Databricks SQL Warehouses, perform query optimization, and utilize internal visualizations for rapid data exploration.
Cloud Infrastructure: Leverage AWS cloud services to manage data storage, compute resources, and secure data movement.
DBA & Performance Tuning: Act as a custodian for our data platform-managing indexing, clustering, vacuuming, and performance tuning across both Delta Lake and relational/warehouse environments to ensure cost-efficiency and high speed.
Data Modeling: Design data models (Star Schema / Snowflake) in the Gold layer to ensure optimal performance for BI tools (e.g., Power BI, Tableau).
Data Governance: Manage metadata, permissions, and lineage using Unity Catalog and platform-specific access controls.
Quality Control: Implement automated Data Quality tests as an integral part of the CI/CD data pipelines.

Integration into the development team for a core DWH project and various AI projects. Responsibilities include the ingestion of large volumes of new data, followed by deep understanding and analysis of data in close collaboration with Data Scientists. Design, development, and optimization of critical, diverse, and large-scale data pipelines - in both cloud and on-premise environments.



Key Responsibilities:

Take responsibility for the ingestion of large volumes of new data.
Conduct deep understanding and examination of data in close collaboration with Data Scientists.
Design and develop critical, diverse, and large-scale data pipelines and processes.
Deploy and optimize data solutions across both cloud and on-premise environments.

Architectural leadership of the enterprise DWH project in an AWS cloud environment. The role focuses on designing robust data infrastructure, establishing the technological roadmap, and enabling seamless large-scale data processing to support BI and AI initiatives.

Key Responsibilities:

Lead the architectural design and implementation of the new enterprise DWH project.
Design, develop, and optimize complex cloud-based data solutions for processing massive datasets.
Select and implement the optimal AWS services (Redshift, Glue, Athena, EMR) and data formats (Parquet, Iceberg) for the core data stack.
Provide technical leadership, mentorship, and professional guidance to the Data Engineering team.
Collaborate closely with development teams, Data Scientists, and end-users to define requirements and deliver innovative Data and AI solutions.