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محتوای ارائه شده توسط The Data Flowcast. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط The Data Flowcast یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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Why Developer Experience Shapes Data Pipeline Standards at Next Insurance with Snir Israeli

30:28
 
اشتراک گذاری
 

Manage episode 481297778 series 2948506
محتوای ارائه شده توسط The Data Flowcast. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط The Data Flowcast یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

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/

Thanks for listening to “The Data Flowcast: Mastering Apache Airflow® for Data Engineering and AI.” If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss any of the insightful conversations.

#AI #Automation #Airflow #MachineLearning

  continue reading

59 قسمت

Artwork
iconاشتراک گذاری
 
Manage episode 481297778 series 2948506
محتوای ارائه شده توسط The Data Flowcast. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط The Data Flowcast یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

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/

Thanks for listening to “The Data Flowcast: Mastering Apache Airflow® for Data Engineering and AI.” If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss any of the insightful conversations.

#AI #Automation #Airflow #MachineLearning

  continue reading

59 قسمت

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