Week 9/33: Data Structures and Algorithms for Data Engineering Interviews

Understanding Fundamental Data Structures and Algorithms Practices

In Data Engineering interviews, coding assessments generally fall into two categories:

• Real-World Coding Tasks – Practical problems involving data transformation, file handling, API integrations, and processing large datasets. These are commonly used in mid-sized tech companies, startups, and cloud-based data roles.

• LeetCode-Style Algorithmic Challenges – Traditional Data Structures & Algorithms (DSA) problems, often used by large tech firms (FAANG, Fortune 500) in their screening rounds. These focus on optimising memory and computation efficiency and are typically part of online coding assessments.

While most companies now prioritise real-world problems, some big tech firms still assess algorithmic skills. That’s why understanding fundamental Data Structures and Algorithms is crucial for Data Engineers (if such companies are within our scope), even if the focus is more on practical applications than competitive programming.

What This Post Covers

This post focuses on essential Data Structures & Algorithms Interview Questions for Data Engineering Interviews, breaking down each question in a structured approach:

1. Thinking Steps – Understanding the problem, constraints, and approach

2. Solution Code – Writing an efficient implementation in Python

3. Explanation – Breaking down the logic, performance, and trade-offs

We’ll tackle real interview questions from big-tech companies like Amazon, Google, Meta, and Microsoft, focusing on scalable solutions relevant to Data Engineering workflows.

We will solve example questions to provide insight into what to expect in such rounds in Data Engineering interviews. However, the key to success is extensive practice and a deep understanding of programming fundamentals. Simply reviewing solutions is not enough, real improvement comes from solving problems independently, analyzing different approaches, and continuously refining problem-solving skills.

Topics Covered in This Post:

• Arrays

• Linked Lists

• Stacks & Queues

• Trees & Graphs

• Sorting & Searching

For the previous posts of this series, check here: [Data Engineering Interview Preparation Series]¹

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Arrays

An array is a data structure that contains a group of elements of the same data type and stores them together in contiguous memory locations.

Arrays can be categorised based on size and dimensions:

1. Based on Size

• Fixed-Size Arrays: Have a predefined size that cannot be changed after allocation. Memory is allocated either at compile-time or runtime.

• Dynamic-Sized Arrays: Can grow or shrink during execution. Memory is allocated dynamically, allowing flexibility.

2. Based on Dimensions

• One-Dimensional (1D) Arrays: A simple list of elements stored in a single row.

• Two-Dimensional (2D) Arrays: Structured as rows and columns, like a table.

• Three-Dimensional (3D) Arrays: A collection of 2D arrays, adding depth.

Arrays Interview Question by Meta²

Given a 2D array of user IDs, find the number of friends a user has. Note that users can have none or multiple friends.