Coursera
4 weeks to complete at 10 hours a week
Build data pipelines that scale to production. Master ingestion, transformation, orchestration, and lakehouse architecture at scale.
Recommended experience: SQL proficiency, Python programming fundamentals, and working knowledge of data pipeline concepts, ETL workflows, and basic cloud storage.
Across ten focused courses, you will master the full data engineering stack: mapping data flows, ingesting from relational databases, streaming platforms & REST APIs, building and transforming modular pipelines, evaluating storage formats, loading warehouses incrementally, implementing SCD2 historical tracking, applying data lake transactions and versioning, building lakehouse architectures, automating workflows with Apache Airflow, and unifying data through SQL MERGE reconciliation and performance tuning.
Coursera brings together a diverse network of subject matter experts who have demonstrated their expertise through professional industry experience or strong academic backgrounds. These instructors design and teach courses that make practical, career-relevant skills accessible to learners worldwide.
By the end of the program, you will be equipped to architect, build, & operate data pipelines from raw ingestion through lakehouse delivery with the reliability and performance that modern analytics infrastructure demands.
Qualification
Course fee
Start date
You will be redirected to the training provider to enquire directly. Workinitiatives is not the course or training provider. We aggregate and list courses only.