AWS Data Engineering Training

Join AWS Data Engineering training covering AWS, go, less, spark, SQL with live instructor-led sessions. This 45+ hour programme is designed to help you design and build data lake architectures on AWS with proper governance. Placement assistance, mock interviews, and industry-recognised certification included.

★4.5(10 reviews)

Enrol Now

Call Now WhatsApp Us

45+

Hours

Modules

Topics

4.5

10 reviews

Intermediate

Level

New

Batches weekly

About AWS Data Engineering Training

What This Training Covers

The AWS Data Engineering Training programme at Tutorsbot spans 45+ hours across 8 structured modules. Every module is built around hands-on projects and real-world scenarios — not slide-heavy theory. Your instructor walks you through each concept with live demonstrations, code reviews, and practical exercises so you can apply what you learn from day one. The curriculum is aligned with current Cloud Computing industry expectations and hiring patterns.

Enrollment & Training Quality

AWS Data Engineering Training is available in 4 flexible learning modes — choose online live classes, classroom, hybrid, self-paced, or one-on-one depending on your schedule. Every batch is limited in size to ensure each learner receives personal attention, code-level feedback, and doubt resolution. Career support and certification are included with every enrolment. Tutorsbot instructors are working professionals who teach from delivery experience, and the training standard stays consistent across all modes and batches.

Course Curriculum

8 modules · 17 topics · 45 hrs

Module 1: AWS Foundations for Data Engineers

7 topics

AWS global infrastructure for data workloads
IAM roles, policies, and least-privilege access for data services
Object storage: tiers, versioning, lifecycle, and event notifications
VPC networking for data services: subnets and security groups
Data lake governance with table-level security controls
Cost optimization with free tier and storage analytics
Hands-on: Set up a secure AWS data environment

Module 2: Serverless ETL and Data Catalog

10 topics

Serverless Spark ETL service architecture and components
Data Catalog: databases, tables, and partition metadata store
Crawlers for auto-detecting schema from storage and databases
Visual ETL designer for drag-and-drop pipeline composition
PySpark transformation scripts with DynamicFrame operations
Job bookmarks for incremental data processing
Workflow orchestration for multi-step ETL pipeline scheduling
Data quality rule-based validation for pipeline reliability
Performance tuning: compute allocation and worker optimization
Hands-on: Build a complete ETL pipeline with data quality checks

Module 3: Data Lake Architecture on Cloud Storage

Topics included

5 more modules available

Enter your details to unlock the complete syllabus

Salary & Career Outcomes

What AWS Data Engineering Training graduates earn across roles and cities

45%

Average salary hike after course completion

42 days

Median time to job offer after graduation

Target Roles & Salary Ranges

Cloud Engineer

0-2 years

₹6L - ₹12L

AWSMicrosoftTCSInfosys

Cloud Architect

3-5 years

₹15L - ₹30L

GoogleAWSDeloitteAccenture

DevOps Engineer

2-4 years

₹10L - ₹22L

FlipkartWiproHCLCapgemini

Salary by City & Experience

City	Fresher	Mid-Level	Senior
Bangalore	₹7L	₹18L	₹35L
Hyderabad	₹6L	₹15L	₹28L
Chennai	₹5.5L	₹14L	₹25L
Pune	₹6L	₹14L	₹26L

Career Progression

Fresher

Cloud Engineer

After completing the course with projects

Cloud Engineer

Cloud Architect

2-3 years of hands-on experience

Cloud Architect

DevOps Engineer

5+ years with leadership responsibilities

Enrol in This Course

All prices inclusive of 18% GST. Same curriculum & certification across all formats. Updated Aug 2026.

✓ 7-day refund guarantee✓ Same certificate for all formats✓ Lifetime access to recordings

Online Live

Live instructor-led sessions from anywhere, with recordings for catch-up.

₹32,000incl. GST

GST ₹4,881 included

EMI from ₹5,333/mo

What Our Learners Say

Real feedback from AWS Data Engineering Training graduates

Philip Mathew

BSc Graduate, Pune

Honestly, I was sceptical about training institutes. But AWS Data Engineering Training at Tutorsbot was different. The curriculum was practical, not textbook-heavy. The mock interviews and resume sessions were a game-changer. Currently working as a cloud computing developer and loving it.

Jennifer Rose

B.Tech CSE Student, Trivandrum

I enrolled in AWS Data Engineering Training training at Tutorsbot right after my graduation. The hands-on project work changed everything — I walked into interviews with a real portfolio instead of just a degree certificate. Got placed within 2 months at ₹5.5 LPA. The instructor knew exactly what interviewers look for.

Grace Paulraj

B.Sc IT Student, Madurai

My college didn't teach AWS Data Engineering Training properly. The Tutorsbot programme covered what 4 years of engineering couldn't — real tools, real projects, real confidence. The placement team connected me with 5 companies. I accepted my first offer within 45 days.

Sumaya Firdous

Associate Analyst, 2 yrs exp, Bangalore

As a working professional, I needed something structured and time-efficient. Tutorsbot's AWS Data Engineering Training programme delivered exactly that. The instructors have real industry experience — not just theoretical knowledge. My manager noticed the difference in my first sprint after the training.

Karthikeyan R.

Software Developer, 3 yrs exp, Chennai

I've been working in IT for 3 years but felt stuck. AWS Data Engineering Training training at Tutorsbot gave me the upskilling I needed. Within a month of completing the course, I got promoted and a 40% salary hike. The weekend batches fit perfectly with my job.

Salman Sheikh

DevOps Engineer, 4 yrs exp, Delhi

Rani Alexander

Team Lead, HCLTech

Tutorsbot's AWS Data Engineering Training corporate programme was exactly what our team needed. The trainer adapted the pace based on our team's existing skills. The hands-on labs were directly applicable to our codebase. Our CTO was impressed with the outcome report.

Anitha Jayaraj

Engineering Manager, TCS

We enrolled a batch of 25 engineers in Tutorsbot's AWS Data Engineering Training programme. The curriculum was customised to our tech stack, the trainers were responsive, and we saw measurable productivity improvements within 6 weeks. Planning to train 3 more batches this year.

Ishaq Hussain

Non-IT to Tech Transition, Hyderabad

I left my mechanical engineering job to switch to tech. Everyone said it was risky at 28. Tutorsbot's AWS Data Engineering Training training made the transition possible — structured curriculum, patient instructors, and actual placement support. Now earning 2× my old salary as a cloud computing professional.

Susan Thomas

Career Switcher (Ex-Banking), Kochi

After a 3-year career break, I was terrified about re-entering tech. The AWS Data Engineering Training programme at Tutorsbot was supportive and practical. The instructor never made me feel behind. I'm now working remotely for a product company, and I owe a lot to this training.

Tools & Technologies

Hands-on with the production stack used in AWS Data Engineering Training

Platform

AAWS Console

Framework

AApache Spark

Orchestration

AApache Airflow

Stream Processing

AApache Flink

CLI

AAWS CLI

IaC

AAWS CloudFormation

Cloud Service

AAWS EC2AAWS S3AAWS LambdaAAWS VPC

Database

AAWS RDS

About AWS Data Engineering Training at TutorsBot

AWS Data Engineering is the complete cloud data stack — from ingestion and ETL through data lake design, warehousing, streaming pipelines, and orchestration. It's available as TutorsBot's flagship AWS Data Engineering Training programme, with live online and classroom batches running weekly. This 60-hour course covers AWS foundations for data engineers, Glue and serverless ETL, S3 data lake architecture, Redshift, Kinesis real-time pipelines, and EventBridge orchestration. It's designed for data professionals and Python developers who want to build production-grade data platforms on AWS — not just understand individual services in isolation.

Why AWS Data Engineering? The Numbers Don't Lie

AWS data engineers are among the best-paid technical professionals in India right now. Mid-level AWS data engineers in Bangalore, Hyderabad, and Pune earn 18–30 LPA. Senior data architects who design complete AWS data platforms command 35–50 LPA. The gap between demand and supply of skilled AWS data professionals is real and persistent. Python developers moving into cloud data earn 40–60% salary increases on average. This is a 60-hour investment that returns measurably within a year for most students.

Trained by Working AWS Data Architects

TutorsBot's AWS Data Engineering trainers are data architects and engineers with 12+ years building production pipelines on AWS. They've designed complete data lakes for banking, healthcare, and retail companies in Bangalore and Hyderabad — Glue ETL jobs processing terabytes daily, Kinesis pipelines handling millions of events per hour, Redshift clusters serving hundreds of concurrent BI queries. Batches are capped at 24. They review your actual pipeline code, Glue job scripts, and data model designs during sessions — the feedback is specific and technical.

Certification That Gets You Hired

TutorsBot's AWS Data Engineering certification requires completing a full data pipeline project: S3-based data lake, Glue ETL, Redshift loading, Kinesis streaming component, and EventBridge-based orchestration. That project is your AWS data portfolio centrepiece. Employers searching for AWS Data Engineering Certification Training holders find TutorsBot graduates consistently among the best-prepared candidates. Data engineering interviews are heavily technical — hiring managers ask you to walk through pipeline designs. This project gives you exactly that to discuss in depth.

AWS Data Engineering Jobs: Market Demand in 2026

AWS data engineering hiring is among the fastest-growing segments in Indian IT. Companies in Bangalore, Hyderabad, and Chennai — fintech, healthtech, retail, and media — all need engineers who can design, build, and maintain end-to-end data pipelines on AWS. The role is hybrid: you need platform knowledge (AWS services), programming ability (Python, SQL), and architectural judgment (when to use Glue vs Lambda, S3 vs Redshift). All three are covered in this course. Demand far exceeds supply of genuinely skilled candidates.

Who Should Join This Course

Python and SQL proficiency are both required — you'll write real Glue ETL scripts and Athena queries throughout. Basic AWS familiarity (S3, IAM, EC2 concepts) is expected. Understanding of data formats and data modelling helps. This is not a beginner course. Data analysts, Python developers, and SQL engineers transitioning to cloud data engineering are the primary audience. If you've written Python scripts against databases and understand what a data pipeline does conceptually, you're ready to start.

What You'll Actually Be Able to Do

You'll design and build data lakes on S3 with proper partitioning and governance. You'll write Glue ETL jobs in Python, configure Glue crawlers and Data Catalog, build Kinesis real-time ingestion pipelines, design and load Redshift data warehouses, orchestrate pipelines with EventBridge, and implement Lake Formation security. Every module produces a working pipeline component — you finish the course with a complete, deployable AWS data platform architecture as your portfolio.

Tools You'll Work With Every Day

Labs use AWS Glue (ETL, crawlers, Data Catalog), Amazon S3 with lifecycle policies, Amazon Athena, Amazon Kinesis Data Streams and Firehose, Amazon Redshift with Spectrum, Amazon EventBridge, AWS Lake Formation, and AWS Step Functions for orchestration. Python is the primary language. You'll also work with Apache PARQUET format conversion, Glue DynamicFrames, and Redshift Spectrum for querying S3 data directly. All exercises run in live AWS accounts against real data sets.

Roles You Can Apply For After Training

AWS Data Engineer, Cloud Data Architect, Data Platform Engineer, Analytics Engineer, and ML Data Engineer are the primary roles. These are concentrated in Bangalore, Hyderabad, Chennai, and Pune at product companies, consulting firms, and enterprise IT departments. Roles matching AWS Data Engineering Training are actively listed on Naukri, LinkedIn, and Glassdoor with consistent demand across major Indian cities. The 60-hour commitment produces a level of depth that converts to a genuinely compelling profile — not just familiarity with one or two AWS data services.

Real Students, Real Outcomes

A Python developer from Hyderabad with no cloud background completed this course over 12 weeks. His pipeline project — a complete S3 data lake with Glue ETL and Kinesis streaming — became his interview centrepiece. He moved from a 9 LPA development role to a 17 LPA data engineering position at a fintech company. Another student from Bangalore was already working in analytics but on on-prem tools. She added AWS data engineering to her profile and moved to a 22 LPA cloud data architect role. The project portfolio did the convincing in both cases.

What You Get After Completion

Every graduate receives a verified certificate, a portfolio of real projects, and dedicated career support.

Industry-Recognised Certificate

Earn a verified Tutorsbot certificate for AWS Data Engineering, validated through project submissions and assessments.

LinkedIn-importable·Permanent shareable URL·PDF download included

Portfolio of Real Projects

Build production-grade projects reviewed by your instructor. Walk through them in any technical interview.

Instructor code-reviewed·GitHub-hosted portfolio·Interview-ready demos

Placement & Career Support

Dedicated career coaching: resume reviews, mock interviews, LinkedIn optimisation, and introductions to hiring partners.

1-on-1 career coaching·Mock interview rounds·Employer connect programme

Hands-On Lab Experience

Practical assignments and lab exercises that simulate real-world scenarios, ensuring you can apply skills from day one.

Cloud lab environments·Scenario-based exercises·Peer collaboration

Meet Your Instructor

Every AWS Data Engineering Training batch is led by a practitioner who teaches from production experience, not textbooks.

Ayesha Begum

Verified

Data Engineering Lead

10+ yrs experience·Worked at Flipkart, Delhivery, Fractal Analytics

Ayesha has architected real-time data pipelines at scale for e-commerce and logistics companies. She specialises in Spark, Kafka, and lakehouse architectures, and is passionate about mentoring women in tech.

How We Teach

Concepts start with a real problem so theory lands in context
Projects reviewed the way a senior colleague reviews pull requests
Every topic includes the kind of questions you'll face in interviews

Hire Trained Talent

Hire AWS Data Engineering Trained Professionals

Our AWS Data Engineering graduates come with verified project experience, industry-standard skills, and are ready to contribute from day one.

Why hire from us

Project-Verified Skills

Assessment-Backed Hiring

Placement-Ready Talent

Project-based portfolios available

IT Training in Major Cities

Frequently Asked Questions

Everything you need to know about AWS Data Engineering Training, answered by our training experts

1What is the fee / cost for AWS Data Engineering training?

TutorsBot's AWS Data Engineering course costs between ₹32,000 and ₹42,000. It's our most comprehensive data programme at 60 hours — covering Glue ETL, S3 data lakes, Redshift, Kinesis streaming, and EventBridge orchestration. Batch size is capped at 24. The investment reflects the depth and the career outcomes we see from completions. If you're in Hyderabad, we also run classroom batches alongside online. Contact us for the next batch date and grouping options.

2What salary can I expect after AWS Data Engineering certification?

AWS data engineers are among the better-paid technical professionals in India. Mid-level AWS data engineers in Bangalore and Hyderabad earn 18–30 LPA. Python developers transitioning into cloud data from non-cloud roles typically see 40–60% salary increases within a year of completing the course and landing their first data engineering role. Senior data architects designing complete AWS data platforms command 35–50 LPA. The 60-hour investment returns measurably fast for most students.

3What topics are covered in the AWS Data Engineering syllabus?

The syllabus covers AWS Foundations for Data Engineers, Serverless ETL and Data Catalog with Glue, Data Lake Architecture on S3 with Lake Formation governance, Cloud Data Warehouse with Redshift, Real-Time Streaming Data Pipelines with Kinesis, and Orchestration and Event-Driven Pipelines with EventBridge and Step Functions. It's 60 hours of structured, project-driven content — every module produces a working pipeline component, not just exercises you discard after class.

4How long does the AWS Data Engineering training take to complete?

The course is 60 hours — our most comprehensive data programme. Weekend batches take 12–14 weeks. Evening batches can complete it in 8–9 weeks. It's a serious time commitment, but 60 hours means you cover full pipeline breadth: ingestion, ETL, storage, warehousing, streaming, and orchestration. Students who treat it seriously over 3 months finish with a complete, deployable AWS data platform project. That's what makes the commitment worth it.

5Is AWS Data Engineering a good choice for freshers with no experience?

It's best suited to freshers with strong Python and SQL already in hand. If you've got Python project experience and SQL database work, you can keep up — the AWS services are taught from scratch. Pure freshers with no Python or SQL background will struggle from Module 2 onwards. If you're a fresh engineer or data analyst with Python and SQL skills, this course is a strong investment. Freshers from this programme who have project portfolios get placed in data engineering roles at 8–12 LPA in Bangalore and Hyderabad.

6What are the prerequisites for AWS Data Engineering training?

Python and SQL proficiency are both required — you'll write Glue ETL scripts and Athena queries from early sessions. Basic AWS familiarity — S3, IAM, EC2 concept-level understanding — is expected. Knowledge of data formats (CSV, JSON, PARQUET) and data modelling helps contextually. No prior Glue, Kinesis, or Redshift experience needed. Data analysts, Python developers, and SQL engineers making the cloud transition are the primary audience. Come with Python confidence; everything else we teach.

7What job roles are available after completing AWS Data Engineering?

Common roles include AWS Data Engineer, Cloud Data Architect, Analytics Engineer, Data Platform Engineer, and MLOps Data Engineer. Bangalore, Hyderabad, and Chennai have the heaviest AWS data engineering hiring in India, concentrated at fintech, healthtech, retail, and media companies. Remote AWS data roles are also active internationally. This is one of the few courses where the portfolio project — a full end-to-end pipeline — directly substitutes for lack of formal work experience in interviews.

8Is AWS Data Engineering certification worth it in 2026?

Very much so. The gap between AWS data engineering demand and qualified candidate supply in India is real and hasn't closed. A 60-hour course that produces a full pipeline portfolio — Glue, Athena, Redshift, Kinesis, and EventBridge all connected — is substantially different from finishing a basic AWS course and claiming data engineering knowledge. The depth matters. Hiring managers ask technical questions about pipeline design decisions, and this course ensures you have specific, defensible answers.

9What is the scope and future demand for AWS Data Engineering professionals?

Excellent. Every organisation processing significant data needs a cloud data platform, and AWS has the dominant market share for those platforms in India. Data engineering roles aren't going away — they're expanding into ML data pipelines, real-time streaming, and event-driven architectures that require more sophisticated skills, not fewer. Bangalore, Hyderabad, and Chennai will continue to be the primary hiring hubs. Engineers who cover the full AWS data stack consistently have shorter job search cycles than specialists in single services.

10Can working professionals complete AWS Data Engineering training alongside their job?

Yes — weekend batches over 12–14 weeks are specifically designed for this. Many of our students are Python developers or data analysts already employed who are upskilling into cloud data engineering. Evening options are available too in Hyderabad. The honest caveat: 60 hours is a real commitment. Students who succeed while working treat their weekends seriously during those 3 months and apply course concepts to personal practice datasets between sessions. Consistent effort over the full duration is what produces the portfolio.

Still have questions?

Cloud Computing