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Updated weekly · Last refresh Oct 17

Swish Analytics Software Engineer Interview Questions

The questions to prepare for a Swish Analytics Software Engineer interview. Questions from real interview reports rank first. Updated daily.

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1
CodingStart here. 3 questions · ~24 min
State Management for Live FeedsMedium

Tests your approach to state management and UI correctness under high-frequency updates in Swish Analytics.

network requestsstate managementperformance analysisSwish Analytics
D3 With React Sports VisualsMedium

Tests your ability to build interactive visualizations for complex sports analytics datasets using D3 and React.

javascriptdata visualizationFrameworksSwish Analytics
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2
Behavioral & Leadership12 questions · ~96 min
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3
More topics7 questions · ~56 min
Backend for Real-Time FeedsHard

Tests your ability to build reliable ingestion pipelines for real-time sports data at Swish Analytics.

Data Qualitydata integrationvalidationSwish Analytics
Node.js vs Rust ArchitectureMedium

Tests your systems thinking about runtime, performance, and architecture tradeoffs across Node.js and Rust.

Decision Makingtechnical experiencetechnical depthSwish Analytics
Race Conditions in Odds UpdatesHard

Tests your concurrency control and data consistency strategies for live odds updates in Swish Analytics.

transactionsdata integrityconcurrencySwish Analytics
Secure AWS for Sports APIHard

Tests your ability to design secure, highly available AWS architectures for Swish Analytics sports analytics APIs.

Cloud Security Riskshigh availabilityarchitectureSwish Analytics
Client-Side API Error HandlingEasy

Tests your resilience patterns for client-side error handling in Swish Analytics applications.

error handlingjavascriptjson parsingSwish Analytics
Optimizing MySQL for HistoryHard

Tests your SQL tuning skills for large-scale sports statistics workloads at Swish Analytics.

Performance TuningindexessqlSwish Analytics
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Top-Performing Products QueryMedium
Practice
Practice drill

Rank Tesco products by Q2 revenue using a date-filtered join, aggregation, and RANK window function.

sqlperformance analysisMI SelectTTesco
Refactoring a Slow QueryMedium
Practice
Practice drill

Refactor a slow Candid Health claims query using pre-aggregation, latest-event logic, and monthly payer metrics.

Performance Tuningdatabase optimizationCTEsCandid Health
Query Top Product LinesMedium
Practice
Practice drill

Aggregate production by month and return the top three product lines for each month.

Date FunctionsCTEssqlHoneywell
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