Drill Insight

Drill-Coder

Master Data Engineering Interview with AWS

120+ hours 15+ AWS Services 200+ Actual Interview Questions 400+ Big Data Concepts 20+ Data Sources & Pipelines & Dashboards

Master Data Engineering Interview with AWS

Unlock the secrets of Data Engineering interviews with our comprehensive course. This learning path guides you from foundational SQL & Python programming concepts to cloud data platforms design and data pipeline construction

120+ hours
15+ AWS Services
200+ Actual Interview Questions
400+ Big Data Concepts
20+ Data Sources & Pipelines & Dashboards

You will learn

A solid foundation in SQL and Python fundamentals, crucial for building and optimizing data solutions
Confidence in setting up and using RDBMS clients and Python environments, developing efficient data processing scripts
Proficiency in writing advanced SQL queries and Python scripts, mastering data manipulation, and understanding complex query operations like window functions, CTEs, and stored procedures
Deep understanding of data structures in Python, functional and object-oriented programming to architect robust data solutions
Skills in optimizing SQL queries and understanding execution plans to enhance database performance effectively
A comprehensive understanding of data modeling concepts, including data types, database structures, and relationships. Master the principles of normalization and how they apply to both OLTP and OLAP systems
Deep insights into data warehousing using AWS technologies, learning how to efficiently utilize services like S3 for storage, Redshift for warehousing, and Glue for ETL processes
Skills in designing robust data architectures using both traditional and modern approaches, including star and snowflake schemas
Practical experience with AWS tools for schema evolution, data validation, and data governance, ensuring compliance with industry standards and regulations
Ability to integrate and visualize data using AWS Quicksight, enhancing business intelligence and decision-making processes

Course Highlights

Comprehensive Learning Path

Not about AI or Data Science, it is only about getting an offer!

Variables, Data Types, Functions, Data Structures, Control Flows, Scripts, Subqueries, Common Table Expressions, Window Functions, Stored Procedures
Data Formats, Keys, Normalization, OLTP & OLAP, Conceptual/Logical/Physical Models, Fact & Dimension Tables, Star & Snowflake Schema, ETL Pipelines
Schema Evolution, Data Quality, Data Validation, Data Governance, Data Compliance, BI Integration

SQL & Python

Data Modeling & Data Warehousing

Data Integration and Orchestration

Stage

Stage	SQL & Python	Data Modeling & Data Warehousing	Data Integration and Orchestration
	Variables, Data Types, Functions, Data Structures, Control Flows, Scripts, Subqueries, Common Table Expressions, Window Functions, Stored Procedures	Data Formats, Keys, Normalization, OLTP & OLAP, Conceptual/Logical/Physical Models, Fact & Dimension Tables, Star & Snowflake Schema, ETL Pipelines	Schema Evolution, Data Quality, Data Validation, Data Governance, Data Compliance, BI Integration

Begin a transformative journey in data engineering with this comprehensive course designed to provide a solid foundation in data management techniques and the latest technological tools. Gain mastery over key concepts such as data warehousing, ETL processes, and real-time data handling. Develop the skills needed to solve complex data challenges efficiently and effectively, preparing you for advanced roles in the industry. Completing this course will open doors to new career opportunities, positioning you as a valuable candidate for top technology firms seeking skilled data engineers.

AWS Platform Integration

Understanding data engineering on AWS can transform your technical skills, and we make it engaging and accessible. At Drill Insight, we offer production-ready CloudFormation templates, enabling clients to independently deploy AWS environments for hands-on experience. This approach allows practical exploration of AWS services such as S3, Athena, Lambda, and Glue.

Experience hands-on learning and see data engineering concepts come to life, enabling you to master AWS tools and services in a practical, immersive setting. Embrace this unique opportunity to advance your data engineering capabilities on one of the most widely-used cloud platforms.

Business Thinking and Budget Optimization

Our course teaches you to choose the right data engineering tools for your projects, focusing on cost-effective solutions. Learn to decide between using Lambda for simple tasks, Glue for moderate data volumes, or EMR for large-scale needs based on data size and complexity. This skill helps you manage resources wisely, ensuring you use the appropriate technology to optimize costs and performance effectively.

Deployment Types Pricing Flexibility & Scalability ETL operations Performance

AWS Glue

Serverless

Glue is a fully managed server-less ETL tool by AWS to help crawl, discover and organize data.

High

Pricing is based on DPUs and you are billed by the second for crawlers and ETL jobs.

Flexible

It authors highly scalable ETL jobs for distributed processing on a scale-out Apache environment.

Better

It is ideal for new workloads.

Slower and less stable

It is server-less, so there are no computing resources to configure and manage.

Amazon EMR

Server platform

EMR is a cloud-based managed service for processing and analyzing big data quickly.

Low

Hourly rate depends on the instance type used and you are charged for every second used.

Harder to scale

It allows you to resize your cluster as you seem fit and additionally, configure one or more instance groups for processing.

Not so good

It is often a good replacement for on-premises Hadoop migrations.

Faster and more stable

Provides on-demand infrastructure to analyze huge volumes of data quickly and cost effectively.

Efficient Data System & Platform Design Preparation

With our training, you'll master the essential aspects of data lifecycle management within just a few weeks, focusing on data acquisition, storage, processing, and archiving. This course offers a focused curriculum with real-world data scenarios, tailored to help you tackle the data system design and platform management sections of interviews at leading tech companies like Apple, Google, Meta, Microsoft, and Amazon. By the end, you'll confidently understand key concepts and practices to excel in designing efficient and scalable data systems for any data engineering role.

ACCELERATE THE DATA PIPELINE

Effective Communication & Information Gather Skills

Communication is crucial in data engineering roles, where you must accurately interpret and implement requirements from downstream consumers such as data analysts, data scientists, and business intelligence professionals, as well as stakeholders. Our program provides structured guidance on how to clearly articulate your data strategies, designs, and processes. You'll learn how to use industry-specific terminology and communication patterns to effectively convey your solutions.

This preparation is essential for ensuring alignment and clarity in collaborations with data providers and vendors, enabling you to design and manage data operations and pipelines effectively. Through our course, you'll gain the skills to navigate professional interactions with confidence and precision, ensuring that your data solutions meet both business needs and technical standards.

Comparison between the following

Description a

In our discussion, I touched on the data requirements with the data scientist and assumed that the standard data formats we usually work with would be fine. I didn't delve into specifics about their current project, assuming that any discrepancies could be handled during the data processing stage.

Description b

During our meeting, I asked detailed questions about the data schemas they required, the preferred data formats, and how frequently they needed schema evolution. This helped me to accurately determine the necessary data transformations for the underlying pipelines.

Key Outcomes

Unlock Versatile Career Paths with Our Data Engineering Course!

Data Engineer
Design and manage scalable data architectures for storing and processing large datasets.
Data Analyst
Extract and analyze data to provide insights and inform decision-making.
Data Scientist
Use advanced analytics and machine learning to derive meaningful insights from data.
Machine Learning Engineer
Build and deploy machine learning models for predictive analytics and automation.
AI Engineer
Develop and integrate AI solutions to solve complex business problems using data.
Backend Developer
Build and optimize server-side logic and APIs for efficient data processing and management.

Designer & Lecturer

Successful Stories

3w+ Real Admission Offer

Your guide to IT job hunting

7 years of experience

Student Review

Finding it difficult to land a job after graduation, I decided to switch to the IT industry. I enrolled in an algorithm course, and with the help of Teacher Zack, I went from just memorizing to truly understanding the essence of algorithms. He simplified complex problems and helped me solve them successfully, ultimately leading to me receiving an offer.

Jason Liu
I have a foundation in programming and algorithms. I first encountered DrillInsight because of its question bank, and I must say, the content is excellent. It covers real questions from both major tech companies and non-IT companies. In the end, I successfully passed the interview. Thanks to the teachers for their dedication and help!

Yifan Yao
I am a CS major, strong in programming but weak in algorithms, which made job hunting difficult. I chose an algorithm course, where a full-time teacher taught from the fundamentals, helping me truly understand the 3Ws of algorithms (what, why, when). Beyond the course, the teacher also shared valuable interview tips. The course left a deep impression on me.

Eric Wang