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Updated weekly · Last refresh Aug 30

TechnipFMC Data Engineer Interview Questions

The questions to prepare for a TechnipFMC Data Engineer interview. Questions from real interview reports rank first. Updated weekly.

21questions
~3htotal time
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1
PipelinesStart here. 16 questions · ~139 min
Batch vs Stream Processing Trade-offsMedium

Compare batch and stream processing across latency, complexity, cost, and data quality in a modern analytics pipeline.

InfrastructureStream ProcessingETLTechnipFMC
Real-Time Dashboard Pipeline DesignHard

Approach for building near-real-time dashboard pipelines with streaming, orchestration, and data quality controls.

Stream ProcessingSchedulingDependenciesTechnipFMC
Data Quality and Schema EvolutionMedium

Approach for handling schema changes and data quality checks in a high-volume data lake pipeline.

schema evolutionData ModelingQualityTechnipFMC
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2
Coding3 questions · ~26 min
Time Complexity of Common StructuresMedium

Explain average and worst-case time complexities for arrays, hash tables, linked lists, and trees.

Hash TablesArraysTreesTechnipFMC
Deduplicating Records FunctionMedium

Tests algorithmic thinking and practical handling of duplicates for reliable datasets.

Hash TablesArraysSortingTechnipFMC
Python Data Manipulation LibrariesEasy

Tests knowledge of common Python tooling for data engineering workflows.

Hash TablesArraysTechnipFMC
3
More topics2 questions · ~17 min
Top Customers by Sales RevenueEasy
Practice

Use GROUP BY and SUM to rank the top 10 customers by total revenue from a single sales table.

RankingGroup ByAggregationsTechnipFMC
Staying Current in QAEasy

Tests your continuous learning habits relevant to QA engineering at Nintendo of America.

CommunicationLeadershipOwnershipTechnipFMC

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Hands-on SQL practiceWrite and run real queries in the editor. 2 drills · ~20 min
Monthly Sales Trends by CategoryMedium
Practice
Practice drill

Aggregate monthly sales by product category and use LAG to calculate month-over-month changes.

InfrastructureToolsData WranglingTotal Wine & MoreInc.Benjamin Moore
Contact Center Agent Performance MetricsHard
Practice
Practice drill

Compute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.

ETLAggregationsData ModelingADP
The finish line: interview-readyComplete all 21 questions plus 2 hands-on drills to finish this plan.