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Jul 3, 2024 · Get ready for your data engineering interview with our list of key questions. Covering data modeling, ETL processes, database management, and big data technologies, this guide helps you confidently show your skills and knowledge. Perfect for anyone preparing for a data engineer role.
- What Are The Features of A Physical Data Model?
- What Database Relationships Do You Know?
- How Would You Handle Data Loss During A Migration?
- What Are The Three Types of Data Models?
- What Is Normalization? Denormalization?
- What Are Some Things to Avoid When Building A Data Model?
- Why Are NoSQL Databases More Useful Than Relational Databases?
- How Would You Create A Schema Representing Client Click Data on The Web?
- How Would You Design A Data Mart Or Data Warehouse For A New Online Retailer?
The physical database model is the last step before implementation and includes a plan for how you will build the database. Based on the requirements of the build, the physical model typically differs from the logical data model. Some of the key features of the physical data model include: 1. Specs for all tables and columns 2. Relationships betwee...
With this question, explain the types of relationships you know, and provide examples of the work you’ve done with them. The four main types of database relationships include: 1. 1-to-1- When one entity is associated with another. An example would be each employee associating with a particular department. 2. 1-to-Many- When one entity is associated...
Complex migrations can result in data loss, and data engineering candidates should have ideas for minimizing loss. A few steps you can take to reduce data loss during migration would include: 1. Define the specific data required for migration 2. Avoid migrating data that is no longer needed 3. Profile the data (possibly with a tool) to determine th...
The three most commonly used data models are relational, dimensional, and entity-relationship. However, many others aren’t widely used, including object-oriented, multi-value, and hierarchical. The type of model used defines the logical structure and how it is organized, stored, and retrieved.
Data normalization is organizing and formatting data to appear similar across all records and fields. Data normalization helps provide analysts with more efficient and precise navigation, removing duplicate data and maintaining referential integrity. On the other hand, Denormalization is a database technique in which redundant data is added to one ...
Some of the most common mistakes when modeling data include: 1. Poor naming conventions - Establish a consistent naming convention, which will allow for easier querying. 2. Failing to plan accordingly - Gather stakeholder input and design a model for a specific analytics purpose. 3. Not using surrogate keys - Surrogate keys are always helpful or be...
Compared to relational databases, NoSQL databases have many advantages, including scalability and superior performance. Some of the benefits of NoSQL databases include: 1. Store all types of data (unstructured, semi-structured, and structured data) 2. Simplified updating of schemas and fields 3. Cloud-based, resulting in less downtime 4. Can handle...
This question is more architecture-based and assesses experience within developing databases, setting up architectures, and in this case, representing client-side tracking in the form of clicks. A simple but effective design schema would be to represent each action with a specific label. In this case, it assigns each click event a name or title des...
In addition, you’re tasked with using the star schema for your design. The star schema is a database structure that uses one primary fact table to store transactional data and a smaller table or tables that store attributes about the data. Some key transactional details you would want to include in the model: – orders - orderid, itemid, customerid,...
- DATETIME
- INTEGER
- DATETIME
- VARCHAR
- Tell me about yourself. What they’re really asking: What makes you a good fit for this job? This question is asked so often in interviews that it can seem generic and open-ended, but it’s really about your relationship with data engineering.
- What is a data engineer’s role within a team or company? What they’re really asking: What is a data engineer responsible for? For this question, recruiters want to know that you’re aware of the duties of a data engineer.
- When did you face a challenge in dealing with unstructured data and how did you solve it? What they’re really asking: How do you deal with problems? What are your strengths and weaknesses?
- Walk me through a project you worked on from start to finish. What they’re really asking: How do you think through the process of acquiring, cleaning, and presenting data?
- Explain Data Engineering. Data engineering is a term used in big data. It focuses on the application of data collection and research. The data generated from various sources are just raw data.
- What is Data Modelling? Data modeling is the method of documenting complex software design as a diagram so that anyone can easily understand. It is a conceptual representation of data objects that are associated between various data objects and the rules.
- List various types of design schemas in Data Modelling. There are mainly two types of schemas in data modeling: 1) Star schema and 2) Snowflake schema.
- Distinguish between structured and unstructured data. Following is a difference between structured and unstructured data: Parameter. Structured Data. Unstructured Data.
Jul 22, 2024 · If you are preparing for a data engineering interview, you should be well-versed in general and technical questions that evaluate your experience, problem-solving abilities, and technical skills.
Mar 18, 2024 · General data engineer interview questions. Interviewers want to know about you and why you want to become a data engineer. Data engineering is a technical role, so while you’re less likely to be asked behavioural questions, these higher-level questions might appear early in your interview. 1. Tell me about yourself.
Sep 2, 2024 · What are the most common data engineer interview questions you should be familiar with? General Data Engineer Interview Questions. Usually, interviewers start the conversation with a few more general questions. Their aim is to take the edge off and prepare you for the more complex data engineering questions ahead.
