Amazon · amazon.jobs · checked today
Data Engineer I, Secure Third Party Tools (S3T)
Security Foundations builds solutions that keep Amazon systems and data secure on behalf of our customers. We leverage technologies to solve security challenges at Amazon scale, applying automation and machine learning to reduce manual effort and continuously raise the security bar. Our mission is bold: stay ahead of the curve on security while delighting our customers with world-class products.
Skills, with evidence
- SQL
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, scripting and AWS big data technologies.
must have - AWS
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, scripting and AWS big data technologies.
must have · not practised here - Data modelling
- Experience with data modeling, warehousing and building ETL pipelines
- Python
- Experience with one or more scripting language (e.g., Python, KornShell)
- Spark
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Governance & security
Our customers include end consumers, Amazon businesses leveraging third-party, and internal compliance teams who rely on our services.
not practised here - Machine learning
We leverage technologies to solve security challenges at Amazon scale, applying automation and machine learning to reduce manual effort and continuously raise the security bar.
not practised here - Scala
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
not practised here
Your plan
- The SQL screen: correct, then fast≈ 1 h
SQL
- Line items per orderFoundations
- Average order value by countryFoundations
- Count at the right grainFoundations
- Revenue by buyer countryFoundations
- Join three tables into an order detailFoundations
- Python: the data-wrangling round≈ 2 h
Python
- Clean spreadsheet headers into column namesFoundations
- Events normalization jobFoundations
- List the distinct composite keysFoundations
- Deduplicate rows, first one winsFoundations
- Remove repeats from a sorted list of partitionsFoundations
- Data modelling: the round most people fail≈ 2 h
Data modelling
- Marketplace core entitiesFoundations
- Cinema seat bookingFoundations
- City parking baysFoundations
- Dating app matchesFoundations
- Food delivery ordersFoundations
- Spark: read the plan Spark actually ran≈ 1 h
Spark
- HAVING vs WHERE: where does a filter after groupBy actually run?Foundations
- countDistinct vs approx_count_distinct: what the extra shuffle buysFoundations
- COUNT(*) vs COUNT(column): the null trapFoundations
- Grouping by two columns: what changes in the shuffle?Foundations
- Does the join type change the join strategy?Foundations
- Say it out loud≈ 1 h
20 drills · Foundations≈ 7 hours
Not covered by the plan: AWS, Governance & security, Machine learning, Scala.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 11 dremoved the moment Amazon closes it