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Data Engineering Short Course

Learn data engineering to build the robust pipelines that move, transform, and store data at scale for analytics and machine learning. Data engineers are among the highest-paid tech professionals, responsible for the infrastructure that makes data science possible. This course covers ETL versus ELT processes, data warehouse concepts, batch and streaming processing, SQL for data engineering, data quality, orchestration with Airflow, and star schema modeling.. Master data engineering through bite-sized, swipeable learning tiles — designed for busy people who want to learn on the go.

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About This Data Engineering Course

This Data Engineering short course on SkillTiles breaks down everything you need to know into 10 structured milestones, each packed with bite-sized learning tiles you can swipe through in under 15 seconds each.

Whether you're a complete beginner or looking to refresh your knowledge, this online data engineering course uses AI-powered content to adapt to your learning pace. Each tile delivers a focused concept, example, or quiz — making it perfect for commutes, coffee breaks, or quick study sessions.

Covering 70 key topics across 10 milestones, this course takes you from foundations to practical application. Earn badges as you complete each milestone and track your progress on your learning dashboard.

Course Curriculum

1

Pipeline Fundamentals

ETL, data warehouses, and orchestration

ETL vs ELTdata warehouse conceptsbatch vs streamingSQL for data engineeringdata quality checksAirflow/orchestration basicsdata modeling (star schema)
2

SQL for Data Engineers

Advanced SQL techniques

window functionsCTEs and recursive queriesquery optimizationindexing strategiespartitioning tablesmaterialized viewstransaction management
3

ETL/ELT Pipelines

Extract, transform, load data

ETL vs ELT comparisonextraction patternstransformation strategiesincremental vs full loadsdata validation in pipelineserror handling and retriesidempotent pipelines
4

Data Warehousing

Design analytical data stores

star schema designsnowflake schemaslowly changing dimensionsfact and dimension tablesdata vault overviewSnowflake/BigQuery/Redshiftwarehouse optimization
5

Pipeline Orchestration

Schedule and manage data workflows

Apache Airflow basicsDAG design patternstask dependenciesscheduling strategiesmonitoring and alertingPrefect alternativeorchestration best practices
6

Streaming Data

Process data in real-time

batch vs streamingApache Kafka basicsevent-driven architecturestream processing conceptsexactly-once semanticsKafka Connectreal-time analytics
7

Data Quality

Ensure data reliability

data quality dimensionsdata contractsGreat Expectations librarydata profilingschema validationdata lineage trackingmonitoring data quality
8

Data Storage Formats

Choose the right storage format

Parquet formatAvro and ORCDelta Lakedata lake architectureobject storage (S3)data lakehouse conceptpartitioning strategies
9

Python for Data Engineering

Python tools for data pipelines

pandas for transformationPySpark basicsPolars librarydbt (data build tool)async data processingAPI integration patternstesting data pipelines
10

DE Career & Best Practices

Grow as a data engineer

DE certificationsinfrastructure as codeCI/CD for datadocumentation practicescost optimizationteam collaborationstaying current with DE trends

What You'll Learn in This Data Engineering Course

ETL vs ELT
data warehouse concepts
batch vs streaming
SQL for data engineering
data quality checks
Airflow/orchestration basics
data modeling (star schema)
window functions
CTEs and recursive queries
query optimization
indexing strategies
partitioning tables
materialized views
transaction management

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Ready to master Data Engineering?

Start this data engineering short course today. Swipe through AI-powered tiles, earn badges, and build a daily learning habit — no experience needed.

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