DeepSource Technologies

L1 Data Engineer - Remote

🇯🇴 Віддалено, Йорданія Віддалено Повна зайнятість Опубліковано Тра 24, 2026
Локація Віддалено, Йорданія
Формат роботи Віддалено
Тип зайнятості Повна зайнятість
Мова English
Опубліковано 24 травня 2026 р.
Остання перевірка 31 травня 2026 р.
Контекст JobGrid

Огляд ролі від JobGrid

L1 Data Engineer - Remote at DeepSource Technologies: Віддалено, Йорданія; Повна зайнятість. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.

  • Location and workplace: Віддалено, Йорданія
  • Role classification: Повна зайнятість
  • Source freshness: checked by JobGrid on 2026-05-31.
  • Application path: candidates continue to the employer application page with non-personal referral tags.

We are looking for a motivated and technically solid L1 Data Engineer to join our growing Data & Analytics team. In this role, you will be responsible for designing, building, and maintaining the data architecture and infrastructure that supports our organization's data strategy. You will work hands-on to develop, test, and deploy reliable data solutions — ensuring pipelines are scalable, efficient, and aligned with business requirements.

This is an ideal opportunity for a data professional who is eager to deepen their expertise in cloud-native data platforms, particularly within the Microsoft Azure and Databricks ecosystem, and who thrives in a collaborative, fast-paced environment.

KEY RESPONSIBILITIES

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support business intelligence and analytics use cases.

• Build and optimize data ingestion processes using Azure Data Factory and Databricks, ensuring data quality and consistency across all layers of the data platform.

• Transform and process large datasets using PySpark and Python, applying best practices for performance and maintainability.

• Write and optimize complex SQL queries to support analytical reporting and data validation requirements.

• Collaborate with data architects and senior engineers to implement and maintain data models aligned with organizational standards.

• Monitor, troubleshoot, and resolve pipeline failures and data quality issues, applying root-cause analysis to prevent recurrence.

• Contribute to documentation of data pipelines, data dictionaries, and engineering standards.

• Support the team in exploring and evaluating new tools and approaches to continuously improve the data infrastructure.