Home About Training
Microsoft Azure Amazon Web Services (AWS) Google Cloud Platform (GCP) Databricks Data Engineering & Analytics AI & Machine Learning Business Intelligence & Visualization DevOps Engineering
Role Based Learning Blog Get in Touch
Enterprise Training Databricks Data Engineer Associate

Engineer Modern Data Platforms

Hands-on data engineering training for teams building reliable pipelines, lakehouse platforms and real-time analytics.

Request a proposal View curriculum
Program overview

Build data platforms the business can trust

Practical training that takes data teams from platform architecture to Spark processing, orchestrated pipelines, streaming and governance, using real datasets and production patterns.

  • Design batch, streaming and lakehouse architectures
  • Process data at scale with Spark and SQL
  • Orchestrate, test and monitor production pipelines
Data Engineering & Analytics program overview

Who this is for

Data engineers and architects
Analytics engineering teams
Developers moving into data
Platform teams modernising data stacks
Capability outcomes

What your team will be able to do

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

6core capabilities
OUTCOME 01

Lakehouse architecture

Design platforms that unify storage, processing and analytics.

OUTCOME 02

Spark processing

Transform large datasets with Spark DataFrames and SQL.

OUTCOME 03

Pipeline orchestration

Schedule, retry and monitor pipelines with Airflow.

OUTCOME 04

Streaming

Handle real-time events with Kafka and structured streaming.

OUTCOME 05

Data quality

Add tests and checks so downstream users can trust the data.

OUTCOME 06

Governance

Control access, lineage and cost across the platform.

Curriculum

How the program is structured

Module 01

Data platform foundations

  • Modern data architecture patterns
  • Batch versus streaming
  • Data lake and lakehouse design
  • Storage formats: Parquet and Delta
  • Hands-on lab
    design a reference architecture
Module 02

Processing with Spark

  • DataFrames and Spark SQL
  • Joins and aggregations
  • Performance tuning basics
  • Reading and writing at scale
Module 03

Pipelines and orchestration

  • ELT patterns and incremental loads
  • Orchestration with Airflow
  • Change data capture basics
  • Data quality checks
  • Hands-on lab
    build a scheduled pipeline
Module 04

Streaming and real-time

  • Kafka fundamentals
  • Structured streaming
  • Event-driven design
  • Monitoring streaming jobs
Module 05

Governance and operations

  • Data catalog and lineage
  • Access control and masking
  • Observability and alerting
  • Cost and performance management

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

Apache SparkDatabricksAirflowdbtKafkaSnowflakeBigQuerySQL
2guided labs in this program
01
Module 01 · Data platform foundationsdesign a reference architecture
02
Module 03 · 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

Databricks Data Engineer Associate

Prepares teams for the Databricks Certified Data Engineer Associate exam, with practice assessments and a 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 basic Python is recommended. Spark and pipeline 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 Data Engineering & Analytics program

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

Request a proposal
Enterprise trainingData Engineering & Analytics
Request a proposal