Delivery Hero · api.smartrecruiters.com · checked today
Data Engineer II - (Global Discovery, Consumer)
As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in around 65 countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, headquartered in Berlin, Germany, Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index.
Skills, with evidence
- Airflow / orchestration
Production experience with Airflow and dbt, including system reliability, data quality monitoring, and alerting.
must have - Data quality
Own alerts and grow the maturity of our data quality checks, business-logic validation, and testing suite.
must have - Python
Own a well-defined scope of batch pipelines end-to-end, building new Python workflows and reworking existing ones so they are more reliable, readable, and testable.
must have - SQL
Advanced analytical/OLAP SQL, ideally in BigQuery, including tuning queries for performance and cost.
must have - dbt
Production experience with Airflow and dbt, including system reliability, data quality monitoring, and alerting.
must have - Failure handling
We own the data products behind Discovery analytics, from data quality monitoring to supporting recommendation and ML workflows across several data science teams.
- Streaming
Flink, Kafka) and a clear view of batch vs.
- GCP
Shape how we use Airflow and dbt to define, build, and operate the Unified Data Layer, keeping BigQuery workloads efficient and cost-aware.
not practised here - Cost & performance
Advanced analytical/OLAP SQL, ideally in BigQuery, including tuning queries for performance and cost.
Your plan
- The SQL screen: correct, then fast≈ 1 h
Data quality · SQL
- Average order value by countryFoundations
- Line items per orderFoundations
- Revenue by buyer countryFoundations
- Customers who never orderedFoundations
- Hiring funnel by roleFoundations
- 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≈ 1 h
dbt
- Addresses that stay true to the pastIntermediate
- Pipeline design: safe to run twice≈ 3 h
Airflow / orchestration · Failure handling · Streaming
- After the first one finishesFoundations
- Run it for last TuesdayFoundations
- The history nobody keptFoundations
- The spreadsheet is a dependencyFoundations
- Too slow by morningFoundations
- Spark: read the plan Spark actually ran≈ 2 h
Cost & performance
- HAVING vs WHERE: where does a filter after groupBy actually run?Foundations
- partitionBy("country"): what does partition pruning look like in the plan?Foundations
- Predicate pushdown: equality, ranges, and the filter that cannot be pushedFoundations
- Revenue by country: read the DAG behind one groupByFoundations
- Too many small files: where do they cost you, and how does compaction help?Foundations
- Say it out loud≈ 1 h
21 drills · Foundations + Intermediate≈ 8 hours
Not covered by the plan: GCP.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 11 dremoved the moment Delivery Hero closes it