Databricks & Lakehouse Engineering
Delta Lake, medallion architecture, workflows, Unity Catalog concepts and production-grade lakehouse patterns.
- ✓ Instructor-led live sessions, online or in Bengaluru
- ✓ Hands-on labs in every module
- ✓ Capstone project with trainer review
- ✓ Curriculum customisable for corporate teams
- ✓ Certificate of completion
Next batch: Mon, 30 Nov 2026 · 32 hours · 4 days
Databricks & Lakehouse Engineering
Duration: 32 hours · 4 days
Next batch: Mon, 30 Nov 2026
Format: Online live · Bengaluru classroom
Modules: 8 · Topics: 38
Level: Intermediate
Fee: ₹14,999
Trusted by leading experts
Upcoming batches
Open batches for individuals; corporate batches on your dates.
| Programme | Starts | Mode | Schedule | Duration | |
|---|---|---|---|---|---|
| Databricks & Lakehouse Engineering | Mon, 30 Nov 2026 | Online live | Weekday | 4 days | Enquire |
| Databricks & Lakehouse Engineering | Sat, 30 Jan 2027 | Online live | Weekend (Sat) | 5 Saturdays | Enquire |
Soaring demand, and where it takes you
Lakehouse platforms have become a common choice for unified analytics and AI, increasing demand for engineers skilled on them.
Become an expert
Roles this programme prepares you for:
Become a Lakehouse Engineer
Designs and builds medallion pipelines.
- Navigate the Databricks workspace and compute
- Build Delta Lake tables with ACID guarantees
- Implement bronze, silver and gold layers
About the course
Build lakehouse solutions on Databricks: Delta Lake, the medallion architecture, notebooks and jobs, workflows, Unity Catalog governance concepts and production patterns such as incremental ingestion and optimisation.
Delta Lake, medallion architecture, workflows, Unity Catalog concepts and production-grade lakehouse patterns.
Why should I attend?
Data engineers
Spark developers
Platform teams adopting Databricks
Analytics engineers
Prerequisites
SQL and Python; basic Spark knowledge helpful
Level
Intermediate
Delivery modes, duration and fee
Online live
Instructor-led virtual classroom; weekday (full-day) or weekend (Saturday) batches
Bengaluru classroom
In-person batches at our Bengaluru training venue
On-site at your office
Private corporate batch anywhere in India, scheduled around your teams
Blended
Live sessions plus guided self-paced labs and mentor check-ins
Duration: 32 hours · 4 days
Course fee (open batch): ₹14,999
Corporate / team batches: per-participant or flat batch pricing on request, based on group size, format and customisation.
What will you learn
- Navigate the Databricks workspace and compute
- Build Delta Lake tables with ACID guarantees
- Implement bronze, silver and gold layers
- Ingest incrementally with Auto Loader
- Orchestrate pipelines with Databricks Workflows
- Apply governance concepts with Unity Catalog
Skills you will gain
Delta Lake
Pipelines
Governance
Tools and platforms covered
Databricks
Delta Lake
Apache SparkPySparkCourse curriculum
M01 Lakehouse concepts
- Lake vs warehouse vs lakehouse
- Databricks overview
- Compute options
- Workspace navigation
- Cluster policies
🧪 Hands-on: Set up a workspace project
M02 Delta Lake
- ACID tables
- Time travel
- MERGE and schema evolution
- Liquid clustering
- VACUUM and retention
🧪 Hands-on: Build and update Delta tables
M03 Medallion architecture
- Bronze, silver, gold
- Data quality expectations
- Naming
- Delta Live Tables / Lakeflow concepts
- SCD handling
🧪 Hands-on: Implement three layers
M04 Ingestion
- Auto Loader
- Incremental processing
- Change data
- Change data feed
- Streaming tables
🧪 Hands-on: Ingest files incrementally
M05 Orchestration
- Jobs and Workflows
- Parameters
- Monitoring
- Retries and alerts
- Asset bundles for deployment
🧪 Hands-on: Schedule the pipeline
M06 Governance and optimisation
- Unity Catalog concepts
- Permissions
- OPTIMIZE and Z-ordering
- Lineage
- Cost monitoring
🧪 Hands-on: Secure and optimise tables
M07 Databricks SQL and BI
- SQL warehouses
- Dashboards
- Query performance
- Serving to BI tools
🧪 Hands-on: Build a gold-layer dashboard on a SQL warehouse
M08 Capstone: medallion lakehouse
- Ingest raw data
- Build silver and gold
- Govern
- Present
🧪 Hands-on: Deliver a governed bronze-silver-gold pipeline with jobs
Hands-on projects
Medallion pipeline
An incremental bronze-to-gold pipeline with quality checks and a scheduled workflow.
Why train with us
Built around your stack
Labs and examples adapted to the tools, cloud and data your team actually uses.
Practice-first
Every module ends in a lab, and the course ends with a reviewed capstone.
Practitioner-led
Delivered by Karthick Selvam and vetted specialist trainers from our network.
Visible progress
Attendance, lab completion and assessment results shared with your L&D team.
Certificate of completion
Participants who complete the labs and capstone receive a Learning Dots certificate of completion for Databricks & Lakehouse Engineering. [confirm certificate wording / sample image]
Learner reviews
“[Verified learner review for this course]”
“[Verified learner review for this course]”
Meet your trainer
Karthick Selvam
Founder · Data Engineering Corporate Trainer, Bengaluru
[Trainer bio, experience and areas of expertise]
Frequently asked questions
Do we need our own Databricks workspace?
We can use your workspace or provide a training environment.
Can the curriculum be customised for our team?
Yes. Modules, depth, duration and labs can be tailored to your stack and goals.
What delivery formats are available?
Online live instructor-led sessions, Bengaluru classroom, or on-site at your office.
How do we enquire or book?
Use the enquiry form on this page or the Enquire button next to any batch.
What does it cost?
The open-batch fee is ₹14,999 per participant plus GST. Corporate batches are priced on group size, format and customisation.
How long is the course?
32 hours · 4 days. Corporate batches can be split into half-day sessions.
A closer look
About this course
Build lakehouse solutions on Databricks: Delta Lake, the medallion architecture, notebooks and jobs, workflows, Unity Catalog governance concepts and production patterns such as incremental ingestion and optimisation.
What is Databricks & Lakehouse Engineering?
Delta Lake, medallion architecture, workflows, Unity Catalog concepts and production-grade lakehouse patterns.
Who this course is for
Data engineers, Spark developers, Platform teams adopting Databricks, Analytics engineers.
What you will be able to do
Navigate the Databricks workspace and compute. Build Delta Lake tables with ACID guarantees. Implement bronze, silver and gold layers. Ingest incrementally with Auto Loader. Orchestrate pipelines with Databricks Workflows. Apply governance concepts with Unity Catalog.
Career paths
Roles this course supports include Lakehouse Engineer, Databricks Developer, Data Platform Architect. Lakehouse platforms have become a common choice for unified analytics and AI, increasing demand for engineers skilled on them.
Related courses
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Data Engineering guides
What Is Data Engineering? A Plain-English Guide
Data engineering is the discipline of collecting, moving, transforming and storing data so analysts, applications and AI can use it reliably.
ETL vs ELT: What Is the Difference?
Two patterns for moving and transforming data, differing in where the transformation happens.
Data Lake vs Data Warehouse vs Lakehouse
Three architectures for storing analytical data.
What Is Apache Spark and When Should You Use It?
Apache Spark is an open-source engine for processing large datasets in parallel across a cluster.