Delivery Hero · api.smartrecruiters.com · checked today
Senior Analytics Engineer (Data & Agentic Analytics)
foodpanda is part of the Delivery Hero Group, 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. Headquartered in Berlin, Germany.
Skills, with evidence
- Data modelling
Data Modeling and Architecture: Design, build, and maintain robust and scalable data marts/models that accurately represent business needs and support complex analyses.
must have - Data quality
Establish and enforce data quality standards, implement data validation checks, and ensure data lineage is clearly documented.
must have - SQL
Advanced SQL skills and experience with optimisation and data modeling techniques (e.g., dimensional modeling, star/snowflake schema).
must have - Warehousing
Strong understanding of data warehousing technologies, data transformation tools and ETL/ELT processes.
must have - Python
Proficiency in at least one scripting language (e.g., Python, javascript) is a plus.
- Governance & security
You will also champion data quality, governance, observability, and best practices to ensure our data foundations and Agentic solutions are reliable, trustworthy, and scalable.
not practised here - Cost & performance
Drive the enablement and adoption of agentic analytics tools while establishing evaluation and observability frameworks to track accuracy, cost, latency, and drift for continuous performance optimization.
- Dashboards & BI
Familiarity with data visualization (e.g., Tableau, Looker) and/or analytics enablement tools.
not practised here
Your plan
- The SQL screen: correct, then fast≈ 2 h
Data quality · SQL
- Median delivery time per cityIntermediate
- Bucket deliveries into quartilesIntermediate
- Median order value without a median functionIntermediate
- New and repeat orders by monthIntermediate
- Every order against its customer's averageIntermediate
- Python: the data-wrangling round≈ 3 h
Python
- Diff two snapshots of a tableIntermediate
- Explode an array column into rowsIntermediate
- Flatten nested event payloadsIntermediate
- Keep only the latest row for each eventIntermediate
- Pivot a long metrics table to wideIntermediate
- Data modelling: the round most people fail≈ 3 h
Data modelling · Warehousing
- Addresses that stay true to the pastIntermediate
- Seat holds and the release-night raceIntermediate
- Subscription warehouse grainIntermediate
- Campaign efficiencyIntermediate
- Catalogue: products, variants and sellersIntermediate
- Spark: read the plan Spark actually ran≈ 2 h
Cost & performance
- applyInPandas per country: what Spark ships to Python, and the native rewriteAdvanced
- Filters you wrote in the wrong place: where Catalyst moves themAdvanced
- snappy, gzip or zstd: measure the Parquet codec trade-off yourselfAdvanced
- Find the four suspects in a slow pipeline (one of them is innocent)Advanced
- A filter after a window function: pushed down or not?Advanced
- Say it out loud≈ 1 h
20 drills · Intermediate + Advanced≈ 10 hours
Not covered by the plan: Governance & security, Dashboards & BI.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 3 dremoved the moment Delivery Hero closes it