What metadata is, how data lineage helps with debugging and compliance, what data governance covers, and practices that build trust in data at scale.
How workflow orchestration goes beyond scheduling, what a DAG is, tools like Apache Airflow, and practices for retries, dependencies, and alerting.
What makes a data pipeline scalable: parallel and distributed processing, less data movement, managing compute resources, and designing for change.
How DevOps applies to data engineering: version control for pipelines, CI and automated tests, infrastructure as code, deployment, and incident response.
