reView is amicroservices backend over a graph data layer.
Correctness in our systemdepends not just on API behavior, but on whether data is correctly structured,linked, and queryable across services.
In a regulated-industry product, thedifference between a result that runs and a result that is right is the entirevalue of the platform.Concreteexamples of what that means in practice:• Didthe right nodes and relationships get created across multiple services?
• Doesa multi-step query return the correct result, not just a plausible one?
• Aredata integrity guarantees holding under realistic load and failure conditions?
If testingAPI contracts and data integrity across a graph sounds interesting, this roleis designed for that.Scope• Backendand data-focused testing (not UI-heavy)• Integrationand workflow correctness over broad end-to-end coverage• Deeperperformance and full-system validation evolve over time• Embeddedwith the platform team, pairing closely with backend engineers• Localand test environments are containerized (Docker-based), with shared staging forintegration validationLevelingAt the mid level, you will execute and extend an evolving test strategy.At the senior level, you will shape that strategy and influence how theplatform is built for testability.RequirementsAPI& Service Quality (Primary)Designand maintain automated tests for FastAPI servicesValidaterequest/response schemas, error handling, and auth flowsWritetests across layers: unit tests (targeted handler-level validation),integration tests (service-level using test environments), and API-level smoketests against running servicesPreventregressions across service boundariesIntegration& Workflow Testing (Primary)Buildtests for critical flows (e.g., ingestion → graph → query → result)Validatebehavior under realistic conditions (retries, partial failures,



async flows)Ensureconsistency of data across servicesData& Graph Validation (Targeted but Important)Verifycorrectness of node and relationship creation in Neo4j / MemgraphValidatekey queries and multi-hop traversals against expected outputsDetectissues such as missing or incorrect relationships, duplicate entities, brokenidentity assumptions, and incorrect mappings during ingestionDefineand evolve the approach to graph test fixtures (data seeding, isolation,repeatability)End-to-End& Smoke Testing (Selective)Implementa small number of high-value end-to-end or API-level testsFocuson critical workflows rather than broad UI coverageUsepragmatic approaches (e.g., pytest-driven flows, containerized environments)CI/CD& Quality GatesIntegratetest suites into CI pipelinesDefineand enforce quality gates for merges and releases (coverage thresholds,integration test pass rates, graph-integrity checks)Maintaintest reliability and reduce flakinessPerformance& Reliability (Shared)Runbasic load and stress tests using standard tooling - e.g., recurring load teststo catch regressions in core ingestion and query pathsIdentifyobvious bottlenecks in APIs and graph queriesCollaboratewith engineers on scaling behavior in KubernetesDebugging& Observability (Shared)Uselogs and dashboards (Grafana + Loki) to investigate failuresTraceissues across services and data layersHelpreproduce production issues locally and in test environmentsQualificationsExperiencetesting backend systems (APIs, microservices)Comfortablereading and writing production-quality Python (not just test scripts)Experiencewith pytest or similar frameworksExperiencedesigning integration tests across servicesExperienceworking with CI/CD pipelinesComfortableworking in systems where requirements are incomplete and tests help defineexpected behaviorStrongwritten and spoken English skills for cross-border collaborationPreferred(Not Required)Experiencewith FastAPI or similar Python frameworksExperienceworking in Kubernetes or distributed systemsExperiencetesting data pipelines or ETL workflowsFamiliaritywith graph or query-based systems (e.g., Neo4j, Memgraph, SQL, Cypher)Exposureto load testing tools (any)

📌 Qa Engineer (México)
🏢 Data Squared
📍 México