Data Integration Architect

When to Use

Use this skill when you are designing or evaluating an architecture where multiple specialized data stores need to work together and you must reason about how data flows between them, stays consistent, and remains correct in the face of faults.

Concrete preconditions:

• You have (or are planning) more than one data store: for example, a primary relational database plus a search index, an analytics warehouse, a cache, or a machine learning feature store.
• You need to decide the integration strategy: should writes go to all stores directly, or should one store be the source of truth with others derived from it?
• You need to choose the propagation mechanism: synchronous distributed transactions, change data capture, event sourcing, or batch ETL.
• You need to evaluate a processing architecture: Lambda (separate batch and stream layers), Kappa (unified stream layer), or a single integrated system.
• You have a correctness problem: downstream systems are drifting, duplicate events are being applied, or a system boundary is leaking bugs.

Do not use this skill if you have a single-database workload with no integration requirements — use oltp-olap-workload-classifier and storage-engine-selector instead.

Context and Input Gathering