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Home - Lessons - Data Engineering with Snowflake Training - M6 — Orchestration with Apache Airflow - Backfills and SLAs

Data Engineering with Snowflake Training Backfills and SLAs

Data Engineering with Snowflake Training

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M1 — Snowflake Recap and Project Setup

Snowflake architecture refresher

Account setup and trial

SnowSQL and Snowpark CLI

Project structure

M2 — Snowpipe and Continuous Ingestion

Snowpipe architecture

Auto-ingest and Kafka connector

Snowpipe Streaming

Error handling and offsets

M3 — Medallion with dbt

Bronze, silver and gold

dbt models and snapshots

Incremental and merge strategies

Tests and exposures

M4 — Streams and Tasks for CDC

Streams at table level

Task DAGs and CRON

MERGE-driven incremental loads

Failure handling

M5 — Streaming with Kafka and Snowpipe Streaming

Kafka topic design

Kafka connector configuration

Schema evolution

Backfill strategies

M6 — Orchestration with Apache Airflow

Airflow DAGs and sensors

SnowflakeOperator

Backfills and SLAs

Production-grade Airflow on K8s

M7 — Snowpark for Python and Java

Stored procedures with Snowpark

External functions

M8 — Data Quality and Observability

Soda and Great Expectations

Freshness and volume checks

Alerting with PagerDuty and Slack

M9 — Cost Optimisation and FinOps

Warehouse right-sizing

Resource monitors

Auto-suspend tuning

Cost allocation tags

M10 — CI/CD and IaC for Snowflake

Terraform Snowflake provider

GitHub Actions pipelines

dbt Cloud and dbt Core

Environment promotion

M11 — Security and Sharing

Row-access and masking policies

Secure views and data sharing

Marketplace listings

Audit and compliance

M12 — Capstone and SnowPro Advanced Mocks

End-to-end medallion pipeline

Cost and quality review

SnowPro Advanced mocks

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