📊 High-Demand Role 2026

AWS Data Engineer Training in Hyderabad

Build production-grade data pipelines on AWS — Glue, Redshift, Kinesis, Athena, EMR, Lake Formation. Real datasets. Real pipelines. Real jobs at Hyderabad's top tech companies.

📋 Course Quick Facts

3.5 Months Duration
Online + Offline Mode
8+ Real Projects
5–35 LPA Salary

✅ Free demo · No commitment · Reply in 15 mins

🏆 8+ Years Trainer Experience
📁 8+ Real Data Pipeline Projects
🎓 AWS Data Engineer Certified
💼 100% Placement Support
💰 Salary: 5–35 LPA
Why Data Engineering on AWS

Data Engineers are the Highest-Paid Tech Roles in Hyderabad

Every company in Hi-Tec City and Gachibowli is drowning in data — and they need engineers who can move it, transform it, and make it usable. That's a Data Engineer. And AWS has the most complete toolkit to do that job at scale.

This course doesn't teach you theory about data pipelines — it puts you inside them. You'll process real datasets using AWS Glue ETL, run analytical queries on Redshift and Athena, handle real-time streaming with Kinesis, and build data lakes with Lake Formation.

By the end, you'll have a portfolio of 8+ real data engineering projects that you built yourself, and the skills to walk into any data engineering interview in Hyderabad with confidence.

🎯 Who Should Join This Course?

  • Freshers with basic Python / SQL wanting data engineering roles
  • ETL / BI developers moving to cloud data engineering
  • AWS Cloud engineers wanting to specialise in data
  • DBA / Database admins transitioning to cloud data platforms
  • Anyone preparing for AWS Data Engineer Associate exam
  • Analytics engineers wanting to build data pipelines on AWS

📌 Prerequisites

Basic Python and SQL knowledge is helpful. We cover Python + SQL fundamentals in Module 1, so non-technical backgrounds are welcome too.

Full Curriculum

What You Will Learn

9 modules covering every major AWS data engineering service — structured around real job requirements and AWS Data Engineer exam objectives.

1

Python & SQL for Data Engineering

  • Python fundamentals for data tasks — lists, dictionaries, functions
  • Pandas for data manipulation and cleaning
  • SQL — joins, window functions, CTEs, performance tuning
  • Boto3 — AWS SDK for Python (interacting with S3, Glue, Redshift)
2

AWS Storage & Data Lake Foundation

  • S3 — storage classes, lifecycle policies, data partitioning strategy
  • S3 as data lake foundation — folder structure and naming conventions
  • AWS Lake Formation — governance, data catalog, permissions
  • AWS Glue Data Catalog — databases, tables, crawlers
3

AWS Glue — ETL at Scale

  • Glue ETL jobs — PySpark transforms, DynamicFrame vs DataFrame
  • Glue Crawlers — auto-discovering schema from S3 and databases
  • Glue Workflows and Triggers for orchestration
  • Glue Studio — visual ETL development
  • Data quality checks and error handling in Glue
4

Amazon Redshift — Cloud Data Warehouse

  • Redshift architecture — nodes, slices, distribution styles
  • Loading data with COPY command from S3
  • Redshift Spectrum for querying S3 data directly
  • Redshift Serverless for cost-effective analytics
  • Performance tuning — sort keys, dist keys, vacuum, analyze
5

Amazon Athena — Serverless SQL on S3

  • Athena query engine — columnar formats (Parquet, ORC)
  • Partitioning and compaction for cost and performance
  • Athena Federated Queries — querying RDS, DynamoDB, Redis
  • Athena workgroups and cost controls
  • Connecting Athena to BI tools (QuickSight, Tableau)
6

Amazon Kinesis — Real-Time Streaming

  • Kinesis Data Streams — shards, producers, consumers
  • Kinesis Data Firehose — real-time delivery to S3/Redshift
  • Kinesis Data Analytics — SQL on streaming data
  • Kafka vs Kinesis — when to use what
  • Real-time dashboard project with Kinesis + Lambda
7

Amazon EMR — Big Data Processing

  • EMR cluster setup — master, core, task nodes
  • Apache Spark on EMR — structured streaming, batch jobs
  • Hadoop ecosystem on EMR — Hive, HBase, Presto
  • EMR Serverless — auto-scaling big data without cluster management
  • Cost optimisation — spot instances for EMR
8

AWS Step Functions & Orchestration

  • Step Functions for data pipeline orchestration
  • State machines — sequential and parallel execution
  • Error handling and retries in complex pipelines
  • Integrating Glue, Lambda, Redshift in Step Functions workflows
  • Apache Airflow on MWAA — managed orchestration on AWS
9

Data Quality, Monitoring & Security

  • AWS Glue DataBrew for data profiling and cleaning
  • Great Expectations integration for data quality checks
  • CloudWatch metrics and alarms for pipeline monitoring
  • Data encryption — KMS for S3, Redshift, Glue
  • Column-level and row-level security in Lake Formation
📄 Download Full Syllabus PDF
AWS Data Services

Tools & Services You'll Master

ETL & Transformation

AWS Glue Glue DataBrew Glue Studio PySpark Pandas

Storage & Data Lake

Amazon S3 Lake Formation Glue Data Catalog S3 Glacier

Analytics & Querying

Amazon Redshift Amazon Athena Redshift Spectrum QuickSight

Streaming & Events

Kinesis Data Streams Kinesis Firehose Kinesis Analytics AWS MSK

Big Data & Compute

Amazon EMR Apache Spark Apache Hive Presto MWAA (Airflow)

Security & Orchestration

AWS Lake Formation KMS Step Functions CloudWatch IAM
Hands-On Projects

8+ Real Data Pipeline Projects

🏭

End-to-End ETL Pipeline

Ingest raw CSV/JSON from S3, transform with AWS Glue PySpark jobs, load to Redshift, and visualise in QuickSight — full batch pipeline.

Real-Time Sales Dashboard

Kinesis Data Streams → Lambda → DynamoDB → API Gateway → real-time dashboard. Process 10,000+ events per second.

🏞️

AWS Data Lake Architecture

Design and build a multi-zone data lake (raw → cleansed → curated) with Lake Formation governance, Glue Catalog, and Athena querying.

📈

E-Commerce Analytics Platform

Build a complete analytics platform — order data ingestion, Redshift data warehouse with star schema, Athena for ad-hoc queries.

🔄

Incremental Data Pipeline

Design and implement CDC (Change Data Capture) from RDS MySQL to Redshift using DMS and Glue — incremental loads, not full refreshes.

🌊

Log Analytics with EMR + Spark

Process 100GB+ of web server logs using Apache Spark on EMR, apply sessionisation logic, and store aggregated results in S3 Parquet.

Career Outlook

Data Engineer Salaries in Hyderabad — 2026

ExperienceRoleHyderabad Salary
Fresher (0–1 yr)Junior Data Engineer, ETL Developer₹5–8 LPA
1–3 YearsData Engineer, Cloud Data Engineer₹9–15 LPA
3–5 YearsSenior Data Engineer, Data Architect₹15–22 LPA
5+ YearsData Engineering Lead, Principal Engineer₹22–35 LPA

Start Your Data Engineering Career in Hyderabad

Talk to our trainer directly. Get honest advice on whether this course fits your background and goals.

📍 Ameerpet, Hyderabad · Online Available Across Hyderabad

FAQ

Frequently Asked Questions

AWS Data Engineer training covers building scalable data pipelines on AWS using services like Glue, Redshift, Athena, Kinesis, EMR, and Lake Formation. Our Hyderabad course is 100% hands-on — you build real pipelines from scratch on actual AWS accounts, not demo environments.

Basic Python and SQL knowledge helps, but it is not mandatory. We cover Python and SQL fundamentals in Module 1. Students from non-technical backgrounds in Ameerpet and across Hyderabad have successfully completed this course after the foundation module.

We prepare you for the AWS Certified Data Engineer Associate — the most relevant cert for data engineering launched in 2024. We also cover SAA for a strong foundation. Study materials, practice tests, and exam guidance are all included.

Data Engineers in Hyderabad earn premium salaries: Freshers ₹5–8 LPA, mid-level ₹9–15 LPA, senior roles ₹14–22 LPA, leads/architects ₹20–35 LPA. Companies in Hi-Tec City, Gachibowli, Madhapur, and Ameerpet actively hire data engineers.

Yes! We have live online batches for students from Ameerpet, Hi-Tec City, Gachibowli, and all parts of Hyderabad. Same trainer, same 8+ data pipeline projects on real AWS accounts, same placement support as classroom students.

After completing this course you can target: AWS Data Engineer, Data Pipeline Engineer, Cloud Data Engineer, ETL Developer, Data Platform Engineer, BI Engineer. Companies across Hyderabad are actively hiring with salaries from ₹6–22 LPA.

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