My Senior Data Engineer Interview Experience at SmartNews

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senior data engineerOffer
August 12, 20244 reads

Summary

I recently interviewed for a Senior Data Engineer position at SmartNews, which involved multiple rounds focusing on coding, SQL, system design, and behavioral skills. I successfully received an offer for the role.

Full Experience

I recently went through the interview process for a Senior Data Engineer role at SmartNews, and I wanted to share my experience. The process involved several rounds, focusing on my data engineering skills, system design capabilities, and behavioral aspects.

Application and Initial Screen:

I applied directly through their careers portal. A recruiter reached out within a week to schedule an initial phone screen. This call was primarily about my background, interest in SmartNews, and aligning expectations. It lasted about 30 minutes.

Round 1: Technical Screen - Coding & SQL (45 mins)

This round was with a senior engineer. We started with a quick introduction, and then moved into the technical problems.

  • Coding Problem: The interviewer asked me to write code to find the kth largest element in an unsorted array. I discussed various approaches like sorting, min-heap, max-heap, and quickselect. I implemented the quickselect algorithm in Python and walked through its time and space complexity.
  • SQL Problem: The next question was about SQL. I was given a table Products with columns product_id, product_name, category, and price. The task was to find the top 3 most expensive products in each category. I used window functions (ROW_NUMBER() or RANK()) to solve this.

Round 2: System Design (60 mins)

This round was with an engineering manager. The core problem was to design a real-time analytics dashboard for an e-commerce platform.

  • Problem Statement: Design a system that can collect, process, and display real-time sales and user activity data (e.g., page views, clicks, purchases) for an e-commerce website. The dashboard should show metrics like total sales per minute, top-selling products, active users, etc., with low latency.
  • Discussion: I started with functional and non-functional requirements, considering data sources (webhooks, Kafka), data ingestion (Kafka, Flink/Spark Streaming), data storage (NoSQL for raw data, OLAP DB for aggregated data like ClickHouse/Druid), and dashboarding tools (Grafana). We discussed scalability, fault tolerance, and consistency trade-offs.

Round 3: Behavioral / Leadership Principles (45 mins)

This round was with a director. It focused heavily on behavioral questions and how my past experiences aligned with their company values.

  • Questions:
    • "Tell me about a time you had to deal with ambiguity in a project. How did you handle it?"
    • "Describe a project where you failed. What did you learn?"
    • "How do you prioritize your work when you have multiple competing deadlines?"

Interview Questions (5)

Q1
Kth Largest Element in an Array
Data Structures & AlgorithmsMedium

Given an unsorted array of integers nums and an integer k, return the kth largest element in the array. Note that it is the kth largest element in the sorted order, not the kth distinct element.

Q2
Top 3 Most Expensive Products per Category
OtherMedium

Given a Products table with columns product_id, product_name, category, and price, write a SQL query to find the top 3 most expensive products in each category. If there are ties in price, all products with the same price at the 3rd rank should be included.

Q3
Design a Real-time E-commerce Analytics Dashboard
System DesignHard

Design a system that can collect, process, and display real-time sales and user activity data (e.g., page views, clicks, purchases) for an e-commerce website. The dashboard should show metrics like total sales per minute, top-selling products, active users, etc., with low latency, high scalability, and fault tolerance.

Q4
Dealing with Ambiguity
Behavioral

Tell me about a time you had to deal with ambiguity in a project. How did you handle it?

Q5
Learning from Failure
Behavioral

Describe a project where you failed. What did you learn?

Preparation Tips

My preparation primarily involved grinding LeetCode for coding questions, focusing on medium-to-hard level problems. For SQL, I practiced on HackerRank and LeetCode SQL problems. For system design, I read "Designing Data-Intensive Applications" and watched many YouTube videos on common system design patterns (e.g., GDD, CodeKarle). I also did several mock interviews.

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