Amazon · amazon.jobs · checked today
Data Engineer, Data Infrastructure and Generative Intelligence - AIGC Finance
Amazon is looking for a motivated Data Engineer with strong database, analytical skills and big data technology experience to join the Amazon’s Advertising business. You will be a part of the AIGC DIGI team which supports multiple Ads businesses, including but not limited to Stores (amazon.com), Amazon Business, Devices, Video, and Audio Ads. This is an exciting opportunity to re-envision the data architecture for multiple unique ads businesses and be hands-on to deliver your data solutions end-to-end and bring your impact to the teams immediately.
Skills, with evidence
- Data modelling
Experience with data modeling, warehousing and building ETL pipelines
must have - SQL
1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
must have - Warehousing
Experience with data modeling, warehousing and building ETL pipelines
must have - AWS
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
must have · not practised here - Spark
- Manage AWS resources including EC2, EMR, S3, Glue, Redshift, etc
- Cost & performance
As a key data solution provider, you will be partnering with Finance and Business leaders to design, build, expand and optimize data solutions to ensure data scalability, stability, and accuracy.
- Streaming
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
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
- Data modelling: the round most people fail≈ 2 h
Data modelling · Warehousing
- Marketplace core entitiesFoundations
- Cinema seat bookingFoundations
- City parking baysFoundations
- Dating app matchesFoundations
- Food delivery ordersFoundations
- Pipeline design: safe to run twice≈ 4 h
Streaming
- Which day does it belong to?Foundations
- Parcel tracking pipelineIntermediate
- Five minutes behind the sourceIntermediate
- The source will not let youIntermediate
- The fact arrived firstIntermediate
- Spark: read the plan Spark actually ran≈ 1 h
Spark · Cost & performance
- 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
Not covered by the plan: AWS.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 11 dremoved the moment Amazon closes it