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Enterprise Training Data Engineer Associate

Engineer on the Databricks Lakehouse

Hands-on Databricks training for data engineering teams, from Spark fundamentals to production pipelines and governance.

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Program overview

Build production-grade data pipelines

Hands-on training that takes data teams from Lakehouse fundamentals to Spark processing, Delta Lake, orchestrated pipelines and governance, practised in guided sandbox environments.

  • Process large datasets with Apache Spark and PySpark
  • Manage reliable tables with Delta Lake
  • Schedule, secure and govern pipelines with Workflows and Unity Catalog
Databricks program overview

Who this is for

Data engineers and analysts
Developers moving into big data
Platform teams adopting the Lakehouse
Analytics leads modernising reporting
Capability outcomes

What your team will be able to do

Skills that transfer straight into day-to-day project work.

6core capabilities
OUTCOME 01

Spark at scale

Transform large datasets quickly with Spark DataFrames and SQL.

OUTCOME 02

Delta Lake

Build reliable tables with ACID transactions and time travel.

OUTCOME 03

ETL pipelines

Design incremental, repeatable data pipelines.

OUTCOME 04

Data governance

Secure and track data with Unity Catalog.

OUTCOME 05

SQL analytics

Query and visualise data with Databricks SQL.

OUTCOME 06

Jobs and workflows

Schedule and monitor production pipelines.

Curriculum

How the program is structured

Module 01

Lakehouse and workspace basics

  • Lakehouse architecture overview
  • Workspace, clusters and notebooks
  • Working with files and tables
  • Hands-on lab
    run your first notebook
Module 02

Apache Spark and PySpark

  • DataFrames and transformations
  • Spark SQL
  • Joins, aggregations and window functions
  • Reading and writing common formats
Module 03

Delta Lake

  • Creating and managing Delta tables
  • Updates, deletes and merges
  • Time travel and table history
  • Hands-on lab
    build and optimise a Delta table
Module 04

Pipelines and orchestration

  • Incremental ingestion with Auto Loader
  • Medallion architecture (bronze, silver, gold)
  • Workflows and job scheduling
  • Hands-on lab
    build a scheduled pipeline
Module 05

Governance and exam readiness

  • Unity Catalog and permissions
  • Databricks SQL and dashboards
  • Practice assessments and mock exam

Swipe to switch modules

Hands-on practice

Learn by building

Concepts are applied through guided exercises, so your team practises on the same platforms and tools used on real projects.

Platforms and tools

Databricks WorkspaceApache SparkPySparkDelta LakeSQLUnity CatalogWorkflows
3guided labs in this program
01
Module 01 · Lakehouse and workspace basicsrun your first notebook
02
Module 03 · Delta Lakebuild and optimise a Delta table
03
Module 04 · Pipelines and orchestrationbuild a scheduled pipeline
Engagement model

From skills assessment to lasting capability

  1. Before

    Assess

    We review your team skills and the outcomes the business needs.

  2. Planning

    Tailor

    Scope, labs and schedule are aligned to your roles and stack.

  3. Delivery

    Deliver

    Instructor-led sessions with hands-on labs and live Q&A.

  4. After

    Sustain

    Progress reporting and follow-up support to embed the skills.

Delivered your way

Virtual

Live instructor-led sessions delivered online.

Best for: Teams across locations or time zones

On-site

Delivered at your office or a training venue.

Best for: Teams that want focus away from daily work

Hybrid

A mix of in-person and virtual sessions.

Best for: Larger groups split across locations

Private batches

Cohorts built around your team and schedule.

Best for: Teams that need a custom timeline
Request a proposal
Certification alignment

Data Engineer Associate

Aligned to the Databricks Certified Data Engineer Associate exam, with practice assessments and an exam readiness review.

Practice assessments

Mock exam

Readiness review

FAQ

Common questions

Need something specific for your team?

Talk to an advisor
What prior experience is needed?

Working knowledge of SQL and some Python is helpful. Spark and Lakehouse concepts are covered from the start.

Can the program be tailored to our team?

Yes. We align scope, depth and lab scenarios to your roles, stack and goals before delivery.

How is the program delivered?

Instructor-led, virtually or on-site, for a single team or multiple cohorts, with hands-on labs in dedicated environments.

Is support available after the program?

Yes. Participants receive follow-up support after the sessions to help apply the skills on real projects.

Related programs

Explore more training

Ecosystem

Validated by Industry Leaders.

Google
Amazon AWS
Microsoft
Salesforce
Cisco
Intel
TCS
Infosys
Wipro
Deloitte
Sony
Mercedes
Google
Amazon AWS
Microsoft
Salesforce
Cisco
Intel
TCS
Infosys
Wipro
Deloitte
Sony
Mercedes
Market Validation

What Engineering Leaders Say.

We don't deal in theoretical certifications. Our success is measured entirely by the production readiness and multi-cloud capabilities of the teams we deploy.

"

The production-grade sandbox environments completely changed our upskilling trajectory. Our teams didn't just learn AWS; they built failure-resistant architectures they deployed the very next week.

SJ

Sarah Jenkins

VP of Engineering, CloudOps
"

Moving our entire data pipeline to Databricks seemed impossible. The custom architecture playbooks and telemetry tracking provided by the training team gave us absolute confidence to scale.

MR

Marcus Rodriguez

Lead Data Architect
"

It's rare to find an execution model that skips the high-level fluff. We identified critical skill deficits in week one, and by month three, our internal GenAI integrations were live in production.

AK

Aisha Kapoor

Director of AI Infrastructure

Plan your Databricks program

Share your team goals and we will scope a program around them.

Request a proposal
Enterprise trainingDatabricks
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