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
Luke Ambrosetti developed a Snowflake integration setup and automation framework for Braze Cloud Data Ingestion in the Snowflake-Labs/sf-samples repository. He designed a reproducible pipeline that guides users through creating Snowflake objects, generating sample data, and capturing changes using Snowflake streams. Leveraging Python and SQL scripting, Luke implemented data transformation into Braze-compatible payloads and automated the ingestion process with stored procedures and tasks, enabling seamless end-to-end data flows. His work included comprehensive technical documentation and a notebook, providing a robust blueprint for scalable Braze CDI pipelines. The project focused on foundational engineering, prioritizing automation and onboarding efficiency over bug fixes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
267
Activity Months1
Your Network
329 people
Work 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
Repositories Contributed To
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