Data Engineer – Workania.hu

Cégleírás / Organisation / Department

The world’s largest humanitarian organization, with a network of 192-member National Societies. The overall aim of the organization is “to inspire, encourage, facilitate, and promote at all times all forms of humanitarian activities by National Societies with a view to preventing and alleviating human suffering and thereby contributing to the maintenance and promotion of human dignity and peace in the world.” The organization works to meet the needs and improve the lives of vulnerable people before, during and after disasters, health emergencies and other crises.

Elvárások / Requirements

BSC or MSC degree in the field of Computer Science/Information Systems
Min. 3 years experience as a Data Engineer with data platforms
Good knowledge of data platform technologies, including data ingestion, storage, processing, and analytics.
Experience in database design, data warehousing, and data integration concepts.
Experience in cloud platforms.
Knowledge of big data technologies such as Hadoop and Spark.

Your personality:

Strong strategic and conceptual thinking
Ability to drive results
Developing others
Strong presentation skill
Focused on quality and standards
Teamworker

Amit kínálunk / Offer

Data Platform Strategy and Architecture:

• Take part in the development and maintaintenance of the organization’s data platform strategy and roadmap.

Data Ingestion and Integration:

• Design and implement robust data ingestion processes to acquire data from various
sources (internal and external).
• Define data integration patterns and technologies to ensure smooth data flow into
the platform.
• Establish data quality checks and validation mechanisms during the ingestion process.

Data Storage and Management:

• Determine appropriate data storage technologies and structures (e.g., databases, data
lakes, object storage) based on the organization’s needs.
• Design and implement scalable and reliable data storage solutions.
• Develop data management strategies, including data partitioning, indexing, and
archiving, to optimize performance and storage efficiency.

Data Processing and Analytics:
• Design and implement data processing frameworks and pipelines to transform
and analyze data at scale.
• Select and configure appropriate processing technologies, such as distributed
computing platforms, data processing frameworks, and streaming systems.
• Collaborate with data analysts and data scientists to ensure the platform supports
advanced analytics and machine learning workloads.

Data Security and Governance:
• Define and implement data security measures, including data access controls,
encryption, and data masking.
• Establish data governance frameworks and policies to ensure compliance with data
regulations and privacy requirements.
• Monitor and optimize data platform performance and availability, including disaster
recovery and backup strategies.