IT Career Guides & Free Resources
Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
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GCP Roadmap 2026 for Data Engineers
On Google Cloud the warehouse is the centre of the data stack, so this roadmap starts inside BigQuery, in the free sandbox, and moves outward in seven rings: storage and access, loading, table design, transformation, streaming and operations. Each ring has a build, and the renamed services are listed.
AWS Roadmap 2026 for Data Engineers
What to learn on AWS as a data engineer, in the order data moves through a pipeline: S3 and IAM, Glue and Athena, Glue jobs, Redshift, Step Functions, streaming and governance, with something to build at every stage and a clear test for when you are done.
Kubeflow Pipelines: An Introduction for ML Engineers
Kubeflow Pipelines turns Python functions into containerised steps that pass datasets and models to each other. This introduction builds a four-step training pipeline on real Beijing air-quality data, compiles it, runs it locally in Docker, and shows a data check stopping a run before training.
SQL Optimization for Data Engineers
How to make SQL queries faster with evidence: reading the query plan, a full scan versus a composite index versus a covering index measured in engine steps on 2.9 million real taxi rows, why wrapping a column in a function cost twenty times more work, and the habits that carry over to SQL Server and warehouses.
VPC Basics for Data Engineers on AWS
Data engineers meet Amazon VPC when a job cannot reach a database or times out calling S3. This guide covers the networking behind those failures: CIDR blocks and subnets, what makes a subnet public or private, route tables, NAT gateways, VPC endpoints and security groups, with a small platform network built in code.