Overcoming Data Engineering Challenges at Daiichi Sankyo Europe GmbH with Evgenii Prusov

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

The shift to a unified data platform is reshaping how pharmaceutical companies manage and orchestrate data. Establishing standards across regions and teams ensures scalability and efficiency in handling large-scale analytics.

In this episode, Evgenii Prusov, Senior Data Platform Engineer of Daiichi Sankyo Europe GmbH, joins us to discuss building and scaling a centralized data platform with Airflow and Astronomer.

Key Takeaways:

00:00 Introduction.

02:49 Building a centralized data platform for 15 European countries.

05:19 Adopting SaaS to manage Airflow from day one.

07:01 Leveraging Airflow for data orchestration across products.

08:16 Teaching non-Python users how to work with Airflow is challenging.

12:25 Creating a global data community across Europe, the US and Japan.

14:04 Monthly calls help share knowledge and align regional teams.

15:47 Contributing to the open-source Airflow project as a way to deepen expertise.

16:32 Desire for more guidelines, debugging tutorials and testing best practices in Airflow.

Resources Mentioned:

Evgenii Prusov

https://www.linkedin.com/in/prusov/

Daiichi Sankyo Europe GmbH | LinkedIn

https://www.linkedin.com/company/daiichi-sankyo-europe-gmbh/

Daiichi Sankyo Europe GmbH | Website

https://www.daiichi-sankyo.eu

Apache Airflow

https://airflow.apache.org/

Astronomer

https://www.astronomer.io/

Snowflake

https://www.snowflake.com/

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#AI #Automation #Airflow #MachineLearning