Kinaxis Data Engineer Interview Questions Asked in Recent Interviews

Written by Sakshi Gupta

Reviewed by Andre

Table of contents

Introduction

Interview Topics

The Kinaxis Interview Process

Challenge

Featured Interview Question at Kinaxis

Kinaxis Data Engineer Interview Questions

Discussion & Interview Experiences

Introduction

The Kinaxis Data Engineer interview process appears to span four rounds, though candidate reported timelines from first contact to decision are limited. The process screens for SQL, ETL, and data modeling depth, with technical interviews tied closely to enterprise data workflows rather than consumer product or adtech use cases. Candidates also report a distinct architecture discussion after the coding screen, separating hands on problem solving from higher level system design.

Interview Topics

Click or hover over a slice to explore questions for that topic.

Data Structures & Algorithms

(176)

SQL

(157)

Data Modeling

(30)

Data Pipelines

(19)

Machine Learning

(17)

The Kinaxis Interview Process

Recruiter Screen

The process begins with a recruiter call focused on background, role alignment, and experience with data engineering tools and supply chain or enterprise systems. Candidates describe it as “a basic discussion about my experience and projects,” with light probing into tech stack and prior work. This stage filters for alignment with the role before technical evaluation.

Based on candidate reports

Technical Screening Round

The first technical round evaluates SQL and coding fundamentals, often through live problem solving and discussion of data manipulation. Candidates report being asked to write queries and explain logic, with one noting “SQL questions and some coding basics.” This round establishes core technical competency.

Based on candidate reports

Data Engineering and ETL Round

This round focuses on ETL processes, data pipeline design, and working with large enterprise datasets. Candidates mention questions around data modeling and transformation, with feedback like “they asked about building and maintaining ETL pipelines.” The emphasis is on handling structured data in production systems.

Based on candidate reports

System Design and Architecture Round

Candidates are asked to design scalable data systems, often tied to enterprise or supply chain data workflows. Reports highlight discussions around architecture and performance, with one candidate stating “they wanted a high level system design for data processing.” This stage evaluates system level thinking.

Based on candidate reports

Final Team and Behavioral Interviews

The final stage includes interviews with team members or managers, focusing on collaboration, communication, and experience working in enterprise environments. Candidates describe discussions around project ownership and teamwork, with one noting “they focused on how I worked with teams and handled challenges.” This stage validates team fit.

Based on candidate reports