From disconnected data to confident, explainable decisionsdata2 delivers trustworthy, explainable AI (eXAI) that automates critical workflows and turns complexity into clarity.
Our patented, hallucination-resistant eXAI reView platform harmonizes data across your ecosystem delivering real-time actionable insights.Job DescriptionreView is a microservices backend over a graph data layer.
Correctness in our system depends not just on API behavior, but on whether data is correctly structured, linked, and queryable across services.
In a regulated-industry product, the difference between a result that runs and a result that is right is the entire value of the platform.Concrete examples of what that means in practice:Did the right nodes and relationships get created across multiple services?
Does a multi-step query return the correct result, not just a plausible one?
Are data integrity guarantees holding under realistic load and failure conditions?
If testing API contracts and data integrity across a graph sounds interesting, this role is designed for that.ScopeBackend and data-focused testing (not UI-heavy)Integration and workflow correctness over broad end-to-end coverageDeeper performance and full-system validation evolve over timeEmbedded with the platform team, pairing closely with backend engineersLocal and test environments are containerized (Docker-based), with shared staging for integration 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 the platform is built for testability.RequirementsAPI & Service Quality (Primary)Design and maintain automated tests for FastAPI servicesValidate request/response schemas, error handling, and auth flowsWrite tests across layers: unit tests (targeted handler-level validation), integration tests (service-level using test environments), and API-level smoketests against running servicesPrevent regressions across service boundariesIntegration & Workflow Testing (Primary)Validate behavior under realistic conditions (retries, partial failures, async flows)Ensure consistency of data across servicesData & Graph Validation (Targeted but Important)Verify correctness of node and relationship creation in Neo4j / MemgraphValidate key queries and multi-hop traversals against expected outputsDetect issues such as missing or incorrect relationships, duplicate entities, broken identity assumptions, and incorrect mappings during ingestionDefine and evolve the approach to graph test fixtures (data seeding, isolation, repeatability)End-to-End & Smoke Testing (Selective)Implement a small number of high-value end-to-end or API-level testsFocus on critical workflows rather than broad UI coverageUse pragmatic approaches (e.g., pytest-driven flows,



containerized environments)CI/CD & Quality GatesIntegrate test suites into CI pipelinesDefine and enforce quality gates for merges and releases (coverage thresholds, integration test pass rates, graph-integrity checks)Maintain test reliability and reduce flakinessPerformance & Reliability (Shared)Run basic load and stress tests using standard tooling - e.g., recurring load tests to catch regressions in core ingestion and query pathsIdentify obvious bottlenecks in APIs and graph queriesCollaborate with engineers on scaling behavior in KubernetesDebugging & Observability (Shared)Use logs and dashboards (Grafana + Loki) to investigate failuresTrace issues across services and data layersHelp reproduce production issues locally and in test environmentsQualificationsExperience testing backend systems (APIs, microservices)Comfortable reading and writing production-quality Python (not just test scripts)Experience with pytest or similar frameworksExperience designing integration tests across servicesExperience working with CI/CD pipelinesComfortable working in systems where requirements are incomplete and tests help define expected behaviorStrong written and spoken English skills for cross-border collaborationPreferred (Not Required)Experience with FastAPI or similar Python frameworksExperience working in Kubernetes or distributed systemsExperience testing data pipelines or ETL workflowsFamiliarity with graph or query-based systems (e.g., Neo4j, Memgraph, SQL, Cypher)#J-*****-Ljbffr

📌 Qa Engineer (Estado de México)
🏢 Data2
📍 Estado de México