Amazon · amazon.jobs · checked today
Data Engineer II (1 Year FTC), Supply Chain Optimization Technologies - Planning
**This is a 1 Year FTC contract** Are you passionate about building data solutions that power decisions at massive scale? As a Data Engineer II at Amazon, you will design, build, and optimize data architectures that turn raw information into reliable, high-quality datasets used by analysts, scientists, and engineering teams.
Skills, with evidence
- Data modelling
Create and maintain logical and physical data models that accurately represent business requirements, enforce data integrity, and support downstream analytics and reporting needs.
must have - SQL
Write clean, well-documented code using SQL and scripting languages to automate data processes, optimize query performance, and build tools for tracking data lineage and improving data quality.
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 - Cost & performance
As a Data Engineer II at Amazon, you will design, build, and optimize data architectures that turn raw information into reliable, high-quality datasets used by analysts, scientists, and engineering teams.
- Data quality
- Write clean, well-documented code using SQL and scripting languages to automate data processes, optimize query performance, and build tools for tracking data lineage and improving data quality.
- Failure handling
Afternoons often include design reviews with your team, where you propose improvements to existing architectures or troubleshoot production incidents at their root cause.
- Spark
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Streaming
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Dashboards & BI
You will start your day reviewing pipeline health dashboards and resolving any data quality issues before they reach downstream consumers.
not practised here - Governance & security
- Write clean, well-documented code using SQL and scripting languages to automate data processes, optimize query performance, and build tools for tracking data lineage and improving data quality.
not practised here
Your plan
- The SQL screen: correct, then fast≈ 1 h
SQL · Data quality
- Average order value by countryFoundations
- Line items per orderFoundations
- Revenue by buyer countryFoundations
- Customers who never orderedFoundations
- Hiring funnel by roleFoundations
- 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
- Pipeline design: safe to run twice≈ 3 h
Failure handling · Streaming
- After the first one finishesFoundations
- The history nobody keptFoundations
- The spreadsheet is a dependencyFoundations
- Waiting for the fileFoundations
- Where did the rows go?Foundations
- Spark: read the plan Spark actually ran≈ 1 h
Cost & performance · 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 + Intermediate≈ 8 hours
Not covered by the plan: AWS, Dashboards & BI, Governance & security.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 3 dremoved the moment Amazon closes it