Solution

Data Engineering Capability

Build in-house teams that can design, build and run reliable data pipelines and platforms.

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Why it matters

The case for structured data engineering capability training

Faster delivery

Teams that share common practices ship pipelines and reports faster, with fewer handoffs.

Fewer incidents

Engineering discipline reduces broken jobs and bad data reaching stakeholders.

Retention & growth

Clear learning paths help you grow talent from within.

Batches

Upcoming batches

ProgrammeStartsModeScheduleDuration
Databricks & Lakehouse EngineeringMon, 30 Nov 2026Online liveWeekday
9:30 AM – 5:30 PM IST
4 daysEnquire
Data Engineering FoundationsMon, 14 Dec 2026Bengaluru classroomWeekday
9:30 AM – 5:30 PM IST
5 daysEnquire
Workflow Orchestration with Apache AirflowSat, 19 Dec 2026Online liveWeekend (Sat)
10:00 AM – 5:00 PM IST
4 SaturdaysEnquire
Apache Spark & PySpark for Data EngineersSat, 09 Jan 2027Online liveWeekend (Sat)
10:00 AM – 5:00 PM IST
5 SaturdaysEnquire
Real-Time Data with Kafka & StreamingWed, 13 Jan 2027Bengaluru classroomWeekday
9:30 AM – 5:30 PM IST
3 daysEnquire
Databricks & Lakehouse EngineeringSat, 30 Jan 2027Online liveWeekend (Sat)
10:00 AM – 5:00 PM IST
5 SaturdaysEnquire

Corporate batches for your team can be scheduled on dates that suit you.

Clients

Organisations we have trained

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Enquire

Plan your programme

Tell us about your training need

FAQ

Frequently asked questions

Can the curriculum be customised to our tech stack?

Yes. Every corporate engagement starts with a needs assessment, and modules, labs and capstones are mapped to the tools and cloud your teams actually use.

What delivery formats do you offer?

Live virtual instructor-led training, on-site training at your office in Bengaluru or other Indian cities, and blended formats.

Who delivers the sessions?

Sessions are led by founder Karthick Selvam, a data engineering corporate trainer, and by vetted practitioner trainers from our freelance trainer network.

How do you measure outcomes?

We agree on success measures upfront, typically pre/post assessments, lab completion and capstone evaluation, and share a report with your L&D team.