Why Developer Experience Shapes Data Pipeline Standards at Next Insurance with Snir Israeli

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

Creating consistency across data pipelines is critical for scaling engineering teams and ensuring long-term maintainability.

In this episode, Snir Israeli, Senior Data Engineer at Next Insurance, shares how enforcing coding standards and investing in developer experience transformed their approach to data engineering. He explains how implementing automated code checks, clear documentation practices and a scoring system helped drive alignment across teams, improve collaboration and reduce technical debt in a fast-growing data environment.

Key Takeaways:

(02:59) Inconsistencies in code style create challenges for collaboration and maintenance.

(04:22) Programmatically enforcing rules helps teams scale their best practices.

(08:55) Performance improvements in data pipelines lead to infrastructure cost savings.

(13:22) Developer experience is essential for driving adoption of internal tools.

(19:44) Dashboards can operationalize standards enforcement and track progress over time.

(22:49) Standardization accelerates onboarding and reduces friction in code reviews.

(25:39) Linting rules require ongoing maintenance as tools and platforms evolve.

(27:47) Starting small and involving the team leads to better adoption and long-term success.

Resources Mentioned:

Snir Israeli

https://www.linkedin.com/in/snir-israeli/

Next Insurance | LinkedIn

https://www.linkedin.com/company/nextinsurance/

Next Insurance | Website

https://www.nextinsurance.com/

Apache Airflow

https://airflow.apache.org/

https://www.astronomer.io/events/roadshow/london/

https://www.astronomer.io/events/roadshow/new-york/

https://www.astronomer.io/events/roadshow/sydney/

https://www.astronomer.io/events/roadshow/san-francisco/

https://www.astronomer.io/events/roadshow/chicago/

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#AI #Automation #Airflow #MachineLearning