Who it’s for
Engineers with the listed foundations who want to deepen this skill or apply it in a different stack.
Starting point: IntermediateData engineering & AI · Corporate training
Sample curriculum
Databricks & Azure Databricks
Build lakehouse workflows with Python, SQL, Spark, and Delta Lake, including governance and pipeline delivery.
- Intermediate
- Live online and in person
At a glance
Bring these foundations
- Python and SQL basics; foundational modules can be included for a new team.
Technologies & tools
- Databricks
- Azure Databricks
- PySpark
- Spark SQL
- Delta Lake
- Unity Catalog
A practical destination
Skills to practise.
The sample path works towards these capabilities. Final goals reflect your team’s starting point and agreed scope.
- 01
Use a workspace and Spark to build understandable data transformations.
- 02
Connect Delta Lake and streaming to a reliable pipeline.
- 03
Review governance, job execution and operational evidence.
Sample curriculum
Follow the learning route.
Each module connects the concepts to practical work. Open a module to explore both.
01Module 1Workspace & foundations
Concepts to understand
- Workspace, compute, and notebook workflows
- Python and SQL preparation
- Lakehouse architecture and data ingestion
Practical work
Explore a workspace, read sample data and inspect a notebook result. Explain the roles of storage, compute and the development environment.
Show the result. Explain one decision. Identify what you would improve.
02Module 2Spark transformations
Concepts to understand
- Dataframes and Spark SQL
- Joins, aggregations, and window functions
- Partitioning and performance inspection
Practical work
Transform and join datasets with Spark. Validate a row-count or business rule before accepting the output.
Show the result. Explain one decision. Identify what you would improve.
03Module 3Delta Lake & streaming
Concepts to understand
- Delta tables, schema handling, and MERGE
- Incremental ETL and Structured Streaming
- Declarative pipelines, including Delta Live Tables workflows
Practical work
Build a Delta-based pipeline and explore a streaming update with checkpoints. Explain how a rerun or interruption affects the result.
Show the result. Explain one decision. Identify what you would improve.
04Module 4Governance & delivery
Concepts to understand
- Unity Catalog and access controls
- Jobs, orchestration, and data quality
- CI/CD with Azure DevOps and pipeline review
Practical work
Review catalog access, scheduled jobs and pipeline monitoring. Show how another engineer can find, run and inspect the work.
Show the result. Explain one decision. Identify what you would improve.
A sample project
Bring the skills together.
Build a bronze-to-gold data pipeline with quality checks, incremental processing, and governed access.
Shorter engagements can focus on selected exercises. A larger, learner-owned capstone can be scoped for a longer programme.
Review the work & reasoning
Four useful questions.
- 01
Does the work meet the agreed requirements?
- 02
Can the learner explain the key decisions and trade-offs?
- 03
What happens with invalid input, failure or an unexpected condition?
- 04
What would they change or explore next?
Designed & delivered by Ragav Kumar V.
Training since 2016 · 100+ batches · 3,000+ professionals trained
Live demonstrations, guided exercises, pair work and project reviews connect the concepts to implementation. We agree the goals, starting knowledge, cohort size, delivery and schedule before shaping the final curriculum.
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