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Scaling Airflow for Enterprise Data Platforms at PepsiCo with Kunal Bhattacharya

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内容由The Data Flowcast提供。所有播客内容(包括剧集、图形和播客描述)均由 The Data Flowcast 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

PepsiCo’s data platform drives insights across finance, marketing and data science. Delivering stability, scalability and developer delight is central to its success, and engineering leadership plays a key role in making this possible.

In this episode, Kunal Bhattacharya, Senior Manager of Data Platform Engineering at PepsiCo, shares how his team manages Airflow at scale while ensuring security, performance and cost efficiency.

Key Takeaways:

00:00 Introduction.

02:31 Enabling developer delight by extending platform capabilities.

03:56 Role of Snowflake, dbt and Airflow in PepsiCo’s data stack.

06:10 Local developer environments built using official Airflow Helm charts.

07:13 Pre-staging and PR environments as testing playgrounds.

08:08 Automating labeling and resource allocation via DAG factories.

12:16 Cost optimization through pod labeling and Datadog insights.

14:01 Isolating dbt engines to improve performance across teams.

16:12 Wishlist for Airflow 3: Improved role-based grants and database modeling.

Resources Mentioned:

Kunal Bhattacharya

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

PepsiCo | LinkedIn

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

PepsiCo | Website

https://www.pepsico.com

Apache Airflow

https://airflow.apache.org/

Snowflake

https://www.snowflake.com

dbt

https://www.getdbt.com

Kubernetes

https://kubernetes.io

Great Expectations

https://greatexpectations.io

Monte Carlo

https://www.montecarlodata.com

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

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Artwork
icon分享
 
Manage episode 509844746 series 2948506
内容由The Data Flowcast提供。所有播客内容(包括剧集、图形和播客描述)均由 The Data Flowcast 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

PepsiCo’s data platform drives insights across finance, marketing and data science. Delivering stability, scalability and developer delight is central to its success, and engineering leadership plays a key role in making this possible.

In this episode, Kunal Bhattacharya, Senior Manager of Data Platform Engineering at PepsiCo, shares how his team manages Airflow at scale while ensuring security, performance and cost efficiency.

Key Takeaways:

00:00 Introduction.

02:31 Enabling developer delight by extending platform capabilities.

03:56 Role of Snowflake, dbt and Airflow in PepsiCo’s data stack.

06:10 Local developer environments built using official Airflow Helm charts.

07:13 Pre-staging and PR environments as testing playgrounds.

08:08 Automating labeling and resource allocation via DAG factories.

12:16 Cost optimization through pod labeling and Datadog insights.

14:01 Isolating dbt engines to improve performance across teams.

16:12 Wishlist for Airflow 3: Improved role-based grants and database modeling.

Resources Mentioned:

Kunal Bhattacharya

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

PepsiCo | LinkedIn

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

PepsiCo | Website

https://www.pepsico.com

Apache Airflow

https://airflow.apache.org/

Snowflake

https://www.snowflake.com

dbt

https://www.getdbt.com

Kubernetes

https://kubernetes.io

Great Expectations

https://greatexpectations.io

Monte Carlo

https://www.montecarlodata.com

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

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