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Cracking the Data Engineering Interview

ویرایش:  
نویسندگان: ,   
سری:  
ISBN (شابک) : 9781837630776 
ناشر: Packt Publishing Ltd. 
سال نشر: 2023 
تعداد صفحات: 483 
زبان: English 
فرمت فایل : EPUB (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) 
حجم فایل: 4 Mb 

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فهرست مطالب

Cracking the Data Engineering Interview
Contributors
About the authors
About the reviewers
Preface
   Who this book is for
   What this book covers
   To get the most out of this book
   Download the example code files
   Conventions used
   Get in touch
   Share Your Thoughts
   Download a free PDF copy of this book
Part 1: Landing Your First Data Engineering Job
1
The Roles and Responsibilities of a Data Engineer
   Roles and responsibilities of a data engineer
      Responsibilities
   An overview of the data engineering tech stack
   Summary
2
Must-Have Data Engineering Portfolio Projects
   Technical requirements
   Must-have skillsets to showcase in your portfolio
      Ability to ingest various data sources
      Data storage
      Data processing
      Cloud technology
   Portfolio data engineering project
      Scenario
   Summary
3
Building Your Data Engineering Brand on LinkedIn
   Optimizing your LinkedIn profile
      Your profile picture
      Your banner
      Header
   Crafting your About Me section
      Initial writing exercise
   Developing your brand
      Posting content
      Building your network
      Sending cold messages
   Summary
4
Preparing for Behavioral Interviews
   Identifying six main types of behavioral questions 
to expect
   Assessing cultural fit during an interview
   Utilizing the STARR method when answering questions
      Example interview question #1
      Example interview question #2
      Example interview question #3
      Example interview question #4
      Example interview question #5
   Reviewing the most asked interview questions
   Summary
Part 2: Essentials for Data Engineers Part I
5
Essential Python for Data Engineers
   Must-know foundational Python skills
      SKILL 1 – understand Python’s basic syntax and data structures
      SKILL 2 – understand how to use conditional statements, loops, and functions
      SKILL 3 – be familiar with standard built-in functions and modules in Python
      SKILL 4 – understand how to work with file I/O in Python
      SKILL 5 – functional programming
   Must-know advanced Python skills
      SKILL 1 – understand the concepts of OOP and how to apply them in Python
      SKILL 2 – know how to work with advanced data structures in Python, such as dictionaries and sets
      SKILL 3 – be familiar with Python’s built-in data manipulation and analysis libraries, such as NumPy and pandas
      SKILL 4 – understand how to work with regular expressions in Python
      SKILL 5 – recursion
   Technical interview questions
      Python interview questions
      Data engineering interview questions
      General technical concept questions
   Summary
6
Unit Testing
   Fundamentals of unit testing
      Importance of unit testing
      Unit testing frameworks in Python
      Process of unit testing
   Must-know intermediate unit testing skills
      Parameterized tests
      Performance and stress testing
      Various scenario testing techniques
   Unit testing interview questions
   Summary
7
Database Fundamentals
   Must-know foundational database concepts
      Relational databases
      NoSQL databases
      OLTP versus OLAP databases
      Normalization
   Must-know advanced database concepts
      Constraints
      ACID properties
      CAP theorem
      Triggers
   Technical interview questions
   Summary
8
Essential SQL for Data Engineers
   Must-know foundational SQL concepts
   Must-know advanced SQL concepts
   Technical interview questions
   Summary
Part 3: Essentials for Data Engineers Part II
9
Database Design and Optimization
   Understanding database design essentials
      Indexing
      Data partitioning
      Performance metrics
      Designing for scalability
   Mastering data modeling concepts
   Technical interview questions
   Summary
10
Data Processing and ETL
   Fundamental concepts
      The life cycle of an ETL job
   Practical application of data processing and ETL
      Designing an ETL pipeline
      Implementing an ETL pipeline
      Optimizing an ETL pipeline
   Preparing for technical interviews
   Summary
11
Data Pipeline Design for Data Engineers
   Data pipeline foundations
      Types of data pipelines
      Key components of a data pipeline
   Steps to design your data pipeline
   Technical interview questions
   Summary
12
Data Warehouses and Data Lakes
   Exploring data warehouse essentials for data engineers
      Architecture
      Schemas
   Examining data lake essentials for data engineers
      Data lake architecture
      Data governance and security
      Data security
   Technical interview questions
   Summary
Part 4: Essentials for Data Engineers Part III
13
Essential Tools You Should Know
   Understanding cloud technologies
      Major cloud providers
      Core cloud services for data engineering
      Identifying ingestion, processing, and storage tools
      Data storage tools
   Mastering scheduling tools
      Importance of workflow orchestration
      Apache Airflow
   Summary
14
Continuous Integration/Continuous Development (CI/CD) for Data Engineers
   Understanding essential automation concepts
      Test automation
      Deployment automation
      Monitoring
   Mastering Git and version control
      Git architecture and workflow
      Branching and merging
      Collaboration and code reviews
   Understanding data quality monitoring
      Data quality metrics
      Setting up alerts and notifications
   Pipeline catch-up and recovery
   Implementing CD
      Deployment pipelines
      Infrastructure as code
   Technical interview questions
   Summary
15
Data Security and Privacy
   Understanding data access control
      Access levels and permissions
      Authentication versus authorization
      RBAC
      Implementing ACLs
   Mastering anonymization
      Masking personal identifiers
   Applying encryption methods
      Encryption basics
      SSL and TLS
   Foundations of maintenance and system updates
      Regular updates and version control
   Summary
16
Additional Interview Questions
Index
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