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Data Integration and Flow Design Questions

Design how systems exchange synchronize and manage data across a technology stack. Candidates should be able to map data flows from collection through activation, choose between unidirectional and bidirectional integrations, and select real time versus batch synchronization strategies. Coverage includes master data management and source of truth strategies, conflict resolution and reconciliation, integration patterns and technologies such as application programming interfaces webhooks native connectors and extract transform load processes, schema and field mapping, deduplication approaches, idempotency and retry strategies, and how to handle error modes. Operational topics include monitoring and observability for integrations, audit trails and logging for traceability, scaling and latency trade offs, and approaches to reduce integration complexity across multiple systems. Interview focus is on integration patterns connector trade offs data consistency and lineage and operational practices for reliable cross system data flow.

HardTechnical
65 practiced
Design a persistent identity graph to answer queries such as 'list all accounts currently associated with company X' when identifiers include changing emails, merged user profiles, device IDs, and SSO IDs. Discuss storage choices (graph DB vs RDBMS + indices), merge/update processes, query patterns, and how to scale lookups for interactive dashboards.
EasyTechnical
65 practiced
Explain idempotency in the context of webhook and API-based integrations between marketing tools and CRM. Provide one or two simple examples of idempotency keys and describe the negative business consequences (duplicate deals, double invoices, misstated attribution) of not supporting idempotent consumers.
MediumTechnical
67 practiced
You support a revenue stack composed of 12 SaaS apps and have a constrained budget. Propose a pragmatic, phased plan to reduce integration complexity while preserving core data quality and essential use cases. Include consolidation options, a canonical data model, connector rationalization, and quick wins you would prioritize.
HardTechnical
68 practiced
You're designing the workflow for a deal close that must update CRM opportunity, create an invoice in billing, and update analytics/commission metrics. Describe architecture patterns (orchestration vs choreography), saga/compensation patterns, monitoring and alerting, and how you'd guarantee business correctness and visibility when partial failures occur across SaaS systems.
HardSystem Design
65 practiced
Architect a CDC-to-data-warehouse pipeline for customer records that supports schema evolution and Slowly Changing Dimensions (SCD Type 1 and Type 2). Specify change-capture mechanism, transformation steps, primary and surrogate key strategy, tooling (examples), and how to handle high-throughput updates while keeping query performance acceptable.

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