Arun Kumar
Support Engineer, Infosys
→ Azure Data Engineer, Maersk
7 months₹6.5L → ₹18L
For working professionals · Online + Offline, Bengaluru
Become an Azure Data Engineer
Become an Azure Data Engineer. Live batches for working professionals in Bengaluru, with real pipeline projects and placement support until you are hired.
50+ placed/monthSupport until placedOnline + offline Bengaluru
- You end up as
- Azure Data Engineer
- Duration
- 5–6 months
- Mode
- Online + offline (Bengaluru)
- Mock interviews
- Unlimited
The Azure Data Engineering track takes working professionals from SQL and scripting to owning production pipelines on Azure Data Factory, Databricks and Synapse. It runs five to six months alongside a full-time job, and includes unlimited mock interviews plus placement support until you are hired.
Who this track is for
Support engineers, ETL developers, SQL developers and backend engineers with two or more years of experience who want to own data pipelines rather than tickets.
What you will be able to do
Own the work end to end: design it, build it, explain it in an interview, and keep it running once it is live. Every module ends with something you can show a hiring manager rather than a certificate.
Outcome role and salary range
Azure Data Engineer — typically ₹14L–₹28L for engineers with 3–8 years of experience. Your actual offer depends on your experience, interview performance and the company.
Azure Data FactoryDatabricksPySparkAzure SynapseDelta LakeSQL
Syllabus
5 modules over 5–6 months.
1 Foundations
- SQL for data engineering: windows, CTEs, query plans
- Python for data work: pandas, typing, testing
- Data modelling: star schema, slowly changing dimensions
- Linux, Git and the command line you actually need
2 Azure core
- Storage accounts, ADLS Gen2, containers and access tiers
- Azure Data Factory: pipelines, triggers, parameterisation
- Integration runtimes and self-hosted connectivity
- Key Vault, managed identities and secure configuration
3 Spark and Databricks
- PySpark DataFrames, partitioning and shuffles
- Databricks notebooks, clusters and job orchestration
- Delta Lake: ACID tables, time travel, MERGE
- Performance tuning: skew, broadcast joins, caching
4 Warehouse and serving
- Azure Synapse dedicated and serverless pools
- Incremental loads and change data capture
- Data quality checks and pipeline observability
- Cost control and capacity planning
5 Production practice
- CI/CD for data pipelines with Azure DevOps
- Monitoring, alerting and on-call basics
- Interview system design: designing a pipeline end to end
- Portfolio review and architecture write-ups
Projects you build
Built on real company-style problems, and written up so you can walk an interviewer through them.
Project 1
Incremental ingestion pipeline
Pull from a transactional source into ADLS with watermarking, handle late-arriving records, and prove idempotency on reruns.
Project 2
Databricks transformation layer
Build bronze, silver and gold Delta tables with data quality gates and a documented recovery path for a failed run.
Project 3
Serving layer and cost review
Model a Synapse warehouse for a reporting workload, then cut its running cost and write up what you changed and why.
How the mock interviews work
- 1 You do a first mock early, before you feel ready. It shows you the gap between what you know and what you can say out loud under pressure.
- 2 Weekly mocks with the placement team after that, each one recorded, each one followed by written feedback on what to fix.
- 3 Rounds are modelled on the companies you are actually targeting — the technical round, the system design round and the manager round each get their own preparation.
- 4 There is no cap. Mocks continue until you are clearing real interviews, not until a quota runs out.
Placed from this track
All placements →Fee
Fee & payment
Fee depends on the track and your starting point. EMI options available. We'll walk you through it in your free assessment call — no pressure, no hidden charges.
Book your assessment →FAQ
Questions about this track
Still unsure? A counsellor can answer anything in a free 30-minute call.
Talk to usCan I do this track while working full time?
Yes. Batches run on weekday evenings and weekends, sessions are recorded, and mock interviews are scheduled around your working hours.
What do I need to know before starting the Data Engineering (Azure) track?
Two or more years of work experience and comfort with basic logic. We cover the technical foundations from the start, so you do not need prior experience with these specific tools.
How much does the Data Engineering (Azure) track cost?
It varies by track and your starting point. We share the exact fee and EMI plans in your assessment call, along with what is included.
What happens if I do not clear interviews in the first few attempts?
Mock interviews continue without a cap and placement support runs until you are hired. Most people need several attempts, and the feedback after each one is the point.
Free assessment
Your next role starts with one call.
Not sure which track fits you? Book a free 30-minute assessment.
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Talk to a real counsellor
Your profile, target role and a realistic timeline.
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Get a recommended track
Matched to where you are today, not your current title.
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Know the fee and EMI
No pressure, no hidden charges.
Free · 30-minute call
Book your free assessment
Tell us where you are today and we'll map the right track for you.