Data Engineer (Process Intelligence)

About MDPI

A pioneer in scholarly, open access publishing, MDPI has supported academic communities since 1996. Headquartered in Basel, Switzerland, MDPI has the mission to foster open scientific exchange in all forms, across all disciplines.

We operate currently over 400 diverse, peer-reviewed, open-access journals supported by over 66,000 academic editors. We serve scholars from around the world to ensure the latest research is openly and broadly available.

Besides our main publishing business, we develop and maintain digital platforms and software ranging from scientific exchange platforms to article databases and search engines, all focused on empowering scholars and giving them the best possible product and service. 

Position overview

To support MDPI’s process intelligence efforts in creating dashboards and tailored alerts, we require an experienced data engineer to design and implement scalable data systems, data pipelines and custom alerts. This work is critical in supporting the process governance and auditing of MDPI journals, so MDPI can gain an overview of its editorial processes with data and enable more data-driven decision making. This will result in MDPI having proactive transparent metrics to report internally and externally.

Core Responsibilities

• Develop performant SQL queries and data models leveraging relational databases (MySQL, PostgreSQL) and in-process OLAP engines like DuckDB.
• Data Pipeline Development: design, build and maintain efficient data pipelines using Apache Airflow and Python.
• Design, implement, and maintain stakeholder-specific alerting mechanisms using activity log pipelines and editorial process data.
• Filtering logic, event-based triggers, and automated data quality checks to ensure timely and relevant notifications.
• Data Acquisition: Integrate data from multiple sources using data lakes and warehouses; designing data models to support analytics, ensuring data consistency and reliability.
• Data Monitoring: Help establish monitoring systems to maintain high standards of data quality and availability.

Additional Responsibilities

• Data Modeling: Work on data modelling tasks to support the creation and maintenance of data warehouses.
• Collaboration: Work with other Data Engineers on data related infrastructure projects
• Continuous Improvement: Participate in the optimization of data processes, seeking opportunities to enhance system performance.

Required

• A university degree, ideally in Computer Science or related science, technology or engineering field.
• 2+ years of relevant work experience in data engineering roles.
• Experience in data acquisition, laking, warehousing, modeling, and orchestration.
• Proficiency in SQL and RDBMS (e.g., MySQL, PostgreSQL).
• Experience with OLAP query engines (e.g. DuckDB).
• Familiarity with Apache Airflow
• Experience with Git and Atlassian tools
• Knowledge in common columnar file formats.
• Strong teamwork and communication skills.
• Ability to work independently and effectively organize your time.
• Comfortable working in a diverse, international environment.

Nice to have

• Experience with Linux (Ubuntu/Debian)
• Knowledge in Data partitioning and incremental scalability

Initiatives

At MDPI, we develop and maintain various platforms in order to better serve the scientific community. Please find here-below a list of our main platforms:

https://www.mdpi.com/

https://sciprofiles.com/

https://sciforum.net/

https://www.scilit.net/

https://www.preprints.org/

https://encyclopedia.pub/

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