Just last month I took a trainee through LinkedIn Business Intelligence Engineer (BIE) Full Process Interview. Throughout the experience, LinkedIn's interview style can be described as "gentle but meticulous", not very likely to give particularly tricky questions, but each question is pursued very deeply, especially the project and data processing logic. Below is a complete breakdown of the three rounds of the process.
Trainee background and interview environment
This participant has a fairly typical background:
- Academic background: Master of Science in Data Science (Data Science M.S.) from a leading West Coast university in the United States of America
- past experienceI worked in an e-commerce company as an intern, responsible for user behavior analysis and retention indicator monitoring, familiar with the construction and monitoring of data pipeline.
- technology stack: Python, SQL, Airflow, Tableau, Snowflake, familiar with ETL processing and dashboard building.
The interview format is Online Remote (Remote Interview).The experience was very smooth, with three rounds completed by LinkedIn's official video system.
Each round lasts about 45 minutes, and the interviewers are all from the U.S. headquarters. They speak at a moderate pace, have a friendly attitude, and value candidates who speak logically and think analytically, rather than memorizing eight-legged or rote-memorized algorithms.
Round 1: Phone Screen (initial phone screen)
This round is an HR-led screening, and although it's a traditional "resume Q&A round," LinkedIn's HR asks more detailed questions than the average company.
Focus around the candidate's resume, for example:
- What kind of data pipeline have you built in your projects in the past?
- What are the main tools you use? (Spark / Airflow / Snowflake etc.)
- What is the data magnitude and who maintains the ETL process?
- How do you debug when you encounter pipeline errors or data delays?
The overall feeling is that the candidate is verifying that he or she has actually "done data". If the resume only contains keywords but no details, it's easy to get stuck in the middle of a follow-up question.
It is recommended that students preparing for this round review the logic and key indicators of each data flow in their resumes in advance, and use structured language to make clear the chain of "business objectives → data sources → processing methods → final analysis output".
Round 2: Hiring Manager Round
This round is a solid mix of technical + business exams.
We start with a medium difficulty SQL question, which is not complex, but examines the complete idea of data processing.
Examples:
There is a user click log table containing fields such as user_id, timestamp, action_type, etc. It is required to calculate the activity metrics of different users over a period of time and finally output some kind of statistical aggregation.
Interviewers don't look at how fast you write, they look at you:
- Can you speak clearly about the table structure and desired outcome;
- Will you split the query step by step, organize the logic with CTE or window functions;
- Can you explain why it was written that way.
After the SQL portion, the MANAGER spends most of his time digging deeper into the project.
Ask very detailed questions like:
- What type of users does your product cater to?
- How are your metrics defined? (DAU, retention, conversion?)
- What exactly does the data cleansing process do?
- Have you encountered inconsistent data and how did you handle it?
The overall atmosphere is friendly, but fast paced, and the manager will constantly follow up with questions based on your answers.
Third round: Interview Day (three rounds of interviews)
The final round consisted of three back-to-back interviews, each lasting about 45 minutes, with each interviewer focusing on a different topic:
Session 1: SQL + Data Logic Questions
This round is the most standard BIE technical question, focusing on your SQL proficiency.
The title involves:
- Multi-table join
- Packet Aggregation
- Window function (row_number, rank)
- edge case handling
LinkedIn's SQL questions are generally not tricky, but they do ask for a clear and readable query and an explanation of the thought process.
Session 2: Product and Business Analysis
This round is more like a mini case study.
The interviewer gives a background on a product feature (e.g. membership growth or ad click optimization) and asks you to design an analytical framework, define metrics, identify data sources, and explain how you would evaluate impact.
The focus is on logical integrity - not to write code, but to show the "analytic path of thought".
Session 3: Behavioral Face + Communication Skills
This round favors the Leadership Principle style, with questions like:
- Give an example of how you would resolve a conflict in cross-team collaboration;
- When have you found that the conclusions of a data analysis were contrary to the business assumptions? How did you communicate this?
- Tell us about a data project you led, from definition to landing.
LinkedIn places a high value on "communication and influence". Even if the technology is strong, if you can't speak your analytical logic or can't align with the business side, you'll lose points.
Interview summary
Overall, LinkedIn's BIE interview process was clear and well-paced:
- SQL It's a basic disk that must be solid;
- Project Details It's the key, prepare to go deep;
- Analytical logic and communication skills Decide the final winner.
LinkedIn especially likes candidates who can "tell a story". It's not just about how fast you can write code, it's about how well you can use data to tell the business and explain the impact.
Prepare recommendations
If you are also preparing for LinkedIn BIE or other analytics post interviews, here are a few lessons learned:
- Review each item on your resume: In particular, indicator definitions, data structures, cleaning logic;
- System practice SQL: Practice more LeetCode Database + simulate join/CTE type questions;
- Preparation of business analysis framework: You need to be able to improvise the logic of retention, conversion, and A/B test analysis;
- Mock interviews to practice communication: Don't memorize the answers, but be able to think and speak at the same time.
Programhelp Uncut Online Assist Experience
This participant prepared the entire course with our Programhelp Remote Voice Assist team.
Many students preparing for BIE or Data Analyst positions actually have similar questions:
👉 SQL is written, but not logical;
👉 Projects do a lot of work but don't express business impact;
👉 Interviews are chaotic in pace and easy to get nervous.
Our Remote No-Trace Assists program is designed for these pain points-
Support Real-time voice prompts, answer ideas guidance, logical structure correction, to help you maintain the most natural rhythm and the best state of mind in the formal interview. If you are preparing for LinkedIn, Meta, Amazon or other data analysis post (BIE / Data Analyst / DS), you can learn about our Voice Assist + Mock Real-World Program, which allows you to be truly "fluent, logical and persuasive" in the interview.
