Snowflake-Labs/sf-samples
Jan 2025 – Jan 2025
1 Month active
Languages Used
JSONPythonSQL
Technical Skills
Cloud Data IngestionData EngineeringETLPython ScriptingSQL ScriptingSnowflake
Luke Ambrosetti
PROFILE
Luke Ambrosetti
Developed an end-to-end Snowflake integration and automation framework for Braze Cloud Data Ingestion within the Snowflake-Labs/sf-samples repository. The work centered on delivering a reproducible setup, including a detailed notebook and README, to guide users through creating Snowflake objects, generating sample data, and capturing changes using streams. Leveraging Python and SQL scripting, the solution transformed ingested data into Braze-compatible payloads and automated the ingestion process with stored procedures and tasks. This approach established a scalable blueprint for onboarding and operationalizing Braze CDI pipelines, emphasizing robust data engineering practices and clear technical documentation without addressing bug fixes during the development period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
267
Activity Months1
Your Network
378 peopleWork History
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 summary for Snowflake-Labs/sf-samples. Delivered a Snowflake integration setup and automation for Braze Cloud Data Ingestion (CDI). The work provides a notebook and README to guide users through creating Snowflake objects, generating sample data, capturing changes with streams, transforming to Braze-compatible payloads, and automating ingestion with stored procedures and tasks for end-to-end data flows. The effort lays the groundwork for reproducible, scalable Braze CDI pipelines and accelerates onboarding for new users. No critical bugs fixed this month; focus was on delivering a robust integration blueprint and automation scaffolding. Technologies leveraged include Snowflake, notebooks, streams, stored procedures, tasks, and data transformation pipelines; skills demonstrated include data engineering, technical documentation, and end-to-end automation.
1 Commits • 1 Features
Jan 1, 2025January 2025 summary for Snowflake-Labs/sf-samples. Delivered a Snowflake integration setup and automation for Braze Cloud Data Ingestion (CDI). The work provides a notebook and README to guide users through creating Snowflake objects, generating sample data, capturing changes with streams, transforming to Braze-compatible payloads, and automating ingestion with stored procedures and tasks for end-to-end data flows. The effort lays the groundwork for reproducible, scalable Braze CDI pipelines and accelerates onboarding for new users. No critical bugs fixed this month; focus was on delivering a robust integration blueprint and automation scaffolding. Technologies leveraged include Snowflake, notebooks, streams, stored procedures, tasks, and data transformation pipelines; skills demonstrated include data engineering, technical documentation, and end-to-end automation.
January 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONPythonSQL
Technical Skills
Cloud Data IngestionData EngineeringETLPython ScriptingSQL ScriptingSnowflake
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