On this page
- What the role looks like
- How the hiring process usually runs
- What they test and how to practise it
- Tools and ideas worth knowing by name
- Questions to practise
- Prepare Leadership Principles stories
- Learn from what went wrong
- An 8-week plan
- Mistakes freshers make
- How to talk about your project
- Where to start today
Most guides about getting into a big company are written for software engineers. This one is for a data engineering role: the person who moves data from where it is created to where people can use it. It explains what Amazon interviews usually look like, what to practise, and how to spend 8 weeks. You do not need to know any of this already.
Match your resume to the posting's skills.
Timed coding or SQL, sometimes with work-style questions.
SQL or coding plus a behavioural question.
Technical rounds, each with Leadership Principles questions.
Interviewers share feedback and decide together.
What the role looks like
Amazon hires data engineers and related roles such as business intelligence engineers. The work is building the pipelines and tables that teams use to track orders, deliveries and customer behaviour. Strong SQL matters a lot in these roles, so start there.
Amazon publishes its Leadership Principles, a list of 16 ideas that it uses to describe how it wants people to work. Behavioural questions in interviews are usually tied to them, so you should read the list and prepare examples.
How the hiring process usually runs
Read this as a typical order, not a promise. Some stages are skipped for some roles, and for students the first stage is often an internship application.
- Application. Choose roles that match your skills. A one-page resume that lists SQL, Python and one project is a good start.
- Online assessment. Many candidates report a timed online test with coding or SQL problems and sometimes questions about how you work. Practise solving problems under a timer.
- Phone or video screen. A technical conversation, often SQL or data questions, plus a question about a time you did something. Keep your examples ready.
- Interview loop. Several interviews. Each usually pairs a technical topic with Leadership Principles questions. One interviewer may be a "bar raiser", a person from outside the team who helps keep the hiring standard consistent.
- Decision. Interviewers write feedback and meet to decide. The result can take days or longer.
What they test and how to practise it
Each row is one thing an interviewer wants to see, what to practise for it, and where to practise it here.
| What they check | What to practise | Practise it |
|---|---|---|
| SQL depth | Joins, window functions, CASE, date logic, deduplication | SQL practice |
| Python | Dictionaries, lists, string handling, small file tasks | Python practice |
| Data modelling | Facts and dimensions, what one row means | Star schema vs snowflake |
| Pipelines | Loads that can be rerun, checks on row counts | What is a data pipeline? |
| Leadership Principles | A short real story for each of 6 to 8 principles | Use the story method below |
Tools and ideas worth knowing by name
Many Amazon data roles use Amazon Web Services (AWS), which Amazon publishes openly. Know these by name.
- S3 stores files, such as raw data and Parquet files.
- Redshift is a data warehouse that you query with SQL.
- Glue helps catalogue data and run ETL jobs.
- Athena runs SQL directly on files in S3.
- Kinesis carries streaming events, similar in idea to Kafka.
You do not need to be an expert in any of these. You need to say what each one is for, in one sentence, and show that you can learn it.
Questions to practise
These are the shapes of question to practise, written the way an interviewer might say them. They are not a leaked list. Solve each one yourself first, then check your answer.
- Return each customer's second most recent order.
- Find products whose sales fell for three months in a row.
- Calculate a 7-day moving average of daily orders.
- Find duplicate customer records and keep the newest.
- Group words by their letters so that anagrams end up together.
- A report shows yesterday's revenue as zero. Walk through how you would investigate.
Prepare Leadership Principles stories
Pick 6 to 8 real moments from projects, college or part-time work. For each, write four short parts: the situation, the task you owned, what you did, and the result. This is often called the STAR method. Use "I" for what you did, and include a number if you have one, such as hours saved or rows checked. Practise saying each in about two minutes.
Learn from what went wrong
Several principles are about owning mistakes and learning from them. Have at least one story where something failed and say plainly what you changed afterwards.
An 8-week plan
Study about an hour a day. If you have less time, stretch each row and keep the order.
| Weeks | Focus | What you can do at the end |
|---|---|---|
| 1 to 2 | SQL basics: joins, GROUP BY, NULL | Answer easy SQL questions without looking anything up |
| 3 to 4 | Window functions, CTEs, deduplication | Solve "top N per group" and "latest row per key" questions |
| 5 | Python: dictionaries, loops, strings, files | Solve easy coding questions in about 20 minutes |
| 6 | Pipelines and warehouse ideas | Explain raw, clean and reporting layers and how a rerun stays safe |
| 7 | One project, written up | Walk through the project in 5 minutes and answer "what went wrong?" |
| 8 | Mock interviews for Amazon | Talk through a problem out loud while you solve it |
Mistakes freshers make
- Memorising answers. Interviewers change the data and the wording. Learn why a solution works, not what it looks like.
- Going silent. Say what you are thinking. A wrong answer with clear thinking often scores better than a right answer nobody understood.
- Skipping the checks. After you write a query, say how you would check it: count the rows, look for NULLs, look for duplicates.
- Having no project. One finished project you can explain beats five half-finished ones.
- Not asking questions. If a question is unclear, ask about the data and what one row means. That is what a working data engineer does.
How to talk about your project
Pick one project and prepare a 5-minute story: the problem, the data, the design, one thing that went wrong, and what you would change. Interviewers at any company, including Amazon, tend to spend the most time on "what went wrong", because it shows how you think. Build one from the projects page and write it up with a README.
Where to start today
Open the SQL practice problems, solve three, and write down what confused you. Then pick the Learn track that covers it. A small start today is worth more than a perfect plan next month.