PROJECT 01
Metadata driven ingestion
One ADF pipeline that copies many tables from SQL and a REST API into the lake, driven by a control table.
ADFForEachControl tables
01 / OVERVIEW
What this course is about
This is the full career track. It starts with SQL and Python, then builds the Azure data platform piece by piece: storage, Azure Data Factory, Databricks, Synapse, streaming, security and DevOps. You finish with an end to end project that mirrors real client work, plus CV, LinkedIn and interview preparation. It is the same stack I have used for years building platforms at Algo.
You learn by doing: every week has hands-on exercises on Google Classroom, and every module ends with something you built yourself.
01
Strong SQL and Python
The two languages every Azure data engineering interview tests.
02
Design a data lake
ADLS Gen2 layout, file formats, Delta and secure access.
03
Build ADF pipelines
Metadata driven ingestion, parameters, triggers and monitoring.
04
Process data in Databricks
PySpark, Delta Lake and the medallion architecture.
05
Serve and stream data
Synapse serverless SQL, Event Hubs and real-time processing.
06
Ship like a team
Key Vault, managed identities, Git, CI/CD and monitoring.
02 / CURRICULUM
Week by week
A clear plan from the first session to the last. The pace adapts to you: if you already know a topic we move faster, and if something needs more time we take it.
WEEKS 1 TO 3SQL for data engineering5 topics
- Joins, CTEs and window functions
- Data modelling and star schemas
- Stored procedures and MERGE
- Query tuning basics
- SQL interview practice
WEEKS 4 TO 6Python and PySpark foundations5 topics
- Python basics for data
- pandas for cleaning
- APIs and JSON
- Intro to Spark DataFrames
- Writing clean, testable code
WEEK 7Azure foundations5 topics
- Subscriptions and resource groups
- Microsoft Entra ID and RBAC
- Managed identities
- Azure Key Vault
- Cost management basics
WEEKS 8 TO 9ADLS Gen2 and lake design5 topics
- Hierarchical namespace
- Raw, curated and serving zones
- CSV, Parquet and Delta
- RBAC and ACLs
- Lifecycle policies
WEEKS 10 TO 12Azure Data Factory5 topics
- Linked services and datasets
- Copy activity and mapping data flows
- Parameters and metadata driven pipelines
- Triggers and self-hosted integration runtime
- Monitoring and alerts
WEEKS 13 TO 15Azure Databricks5 topics
- PySpark transformations
- Delta Lake and MERGE
- Medallion architecture
- Unity Catalog
- Running notebooks from ADF
WEEKS 16 TO 17Azure Synapse Analytics5 topics
- Serverless SQL pools
- External tables over the lake
- Dedicated SQL pool concepts
- Synapse pipelines
- Serving data to Power BI
WEEK 18Streaming5 topics
- Azure Event Hubs
- Stream processing options
- Structured Streaming in Databricks
- Windows and late data
- Real-time dashboards
WEEK 19Warehousing patterns5 topics
- Incremental loads and watermarks
- Slowly changing dimensions
- Data quality checks
- Snowflake on Azure overview
- Choosing the right service
WEEK 20Monitoring and governance5 topics
- Azure Monitor and Log Analytics
- Alerts for failures and long runs
- Microsoft Purview overview
- Data security basics
- Runbooks
WEEK 21DevOps for data5 topics
- Git branching for data teams
- ADF Git integration and ARM templates
- Azure DevOps or GitHub Actions
- Dev, test and prod
- Release checklists
WEEKS 22 TO 23Capstone project4 topics
- End to end Azure data platform
- Architecture diagram and documentation
- Presenting your project
- Code review
WEEK 24Career and interviews4 topics
- CV and LinkedIn review
- Azure data engineering interview questions
- System design for data pipelines
- Mock interviews with feedback
03 / PROJECTS
What you will build
Real projects you can put on GitHub and explain with confidence in interviews.
PROJECT 02
End to end lakehouse
ADF ingests, Databricks builds bronze, silver and gold, Synapse serverless serves it and Power BI shows it.
ADFDatabricksSynapse
PROJECT 03
Real-time telemetry
Stream events through Event Hubs into Delta tables and a near real-time dashboard.
Event HubsStreamingDelta Lake
04 / TOOLS
Tools and technologies
The same tools used by data teams in real companies.
Azure Data FactoryADLS Gen2Azure DatabricksAzure Synapse AnalyticsAzure Event HubsAzure Key VaultMicrosoft Entra IDAzure DevOpsSQLPythonPySparkPower BI
05 / IS IT FOR YOU
Who this course is for
Who it is for
- Beginners who want a complete path to a data engineering job
- IT, support and software people switching careers
- SQL and BI developers moving to the cloud
- Graduates aiming for remote Azure roles
What you need
- No prior experience needed, we start with SQL
- A laptop and stable internet
- An Azure free account, I guide the setup
Roles it leads to
- Azure Data Engineer
- Data Engineer
- ETL Developer
- Cloud Data Engineer
06 / HOW YOU LEARN
What you get
Live and one-to-one
Every session is just you and me, never a batch. No recordings, so we can talk openly about your code.
3 sessions a week
Each session is 1 hour 15 minutes, on weekdays, weekends or both. We agree the schedule before starting.
Google Classroom
Assignments, projects, quizzes, interview questions and homework, all organised in one place.
Real projects
You build projects like the ones companies run, and get feedback on your code and design.
Interview preparation
Common questions, live coding practice and mock interviews with honest feedback.
Job placement support
CV, LinkedIn, applications and interviews. I stay with you until you are hired, as long as you do the work.
07 / PRICING
Simple pricing
You pay for your time with me, not per course. All prices are in US dollars.
Estimated total for Azure Data Engineer at the typical pace (6 months)
About 1200 USD
Full refund if it is not right for you after the first session. Go faster and it costs less.About 1200 USD
08 / YOUR MENTOR
Hikmat Ullah
Senior Data Engineer at Algo · Lahore, Pakistan
I build data platforms with Snowflake, Azure Databricks, Azure Data Factory and Microsoft Fabric every day, and I have been mentoring since 2021. I teach what I use at work, and I stay with you until you land the job.
7+years in data
100+students trained
80+placed in jobs
1:1always, never a batch
09 / FAQ
Questions about Azure Data Engineer
Why 6 months?+
Because it covers everything a junior to mid Azure data engineer needs, starting from zero. If you already know SQL or Python, we skip ahead and it takes less time.
Which certification should I take?+
Microsoft retired DP-203 in 2025. I usually suggest DP-900 for basics and DP-700 or the Databricks Data Engineer Associate later, depending on the jobs you target.
Will this really get me a job?+
The job placement guarantee applies here too: as long as you attend sessions and complete assignments and projects, I keep helping you with CV, LinkedIn, mock interviews and applications until you are hired.
How much does it cost?+
200 USD per month whichever course you choose. You can also pay 100 USD every 15 days or 50 USD per week. All prices are in US dollars wherever you live.
What is the refund policy?+
If the training is not right for you after the first session, you get a full refund. After that, payments already used for completed sessions are not refunded, but unused prepaid time can be refunded.
Is there a job guarantee?+
Yes. As long as you attend your sessions and complete the assignments and projects, I keep helping you with CV, LinkedIn, mock interviews and job applications until you are hired.
Can I join from another country or time zone?+
Yes. Students join from many countries. We pick session times that work for your time zone before we start.
10 / KEEP GOING
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View course → 3 monthsSnowflake Developer
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View course →START WHEN YOU ARE READY
Start the Azure Data Engineer course
Tell me your goals and your time zone. We plan your schedule together, and your first session can start this week.