Project Description:
We build an in-house trading platform covering order management, execution, and data analysis. It runs on a distributed, event-driven backend.
We're hiring a hands-on SDET to own backend test automation: service, integration, contract, data, resilience and performance testing across the platform. You'll co-architect and co-own a unified testing framework with our UI SDET. It covers UI, API, messaging, data and performance tests in one place.
Responsibilities:
Co-architect and co-own, with our UI SDET, a unified testing framework that covers every area we test:
Shared foundations: fixtures, test data, configuration, environments and reporting are shared across REST, WebSocket, Kafka, database, performance and UI suites.
Cross-layer scenarios: one scenario can follow a workflow from the UI through services and events to the database.
One quality view: results from every suite feed a single view of release quality.
Design and build automated service, integration and contract tests for REST APIs, WebSocket services, and Kafka producers and consumers.
Test event-driven flows end to end: message ordering, idempotency, at-least-once and exactly-once semantics, replays, offset handling, dead-letter queues, and schema evolution (Avro, Protobuf, JSON Schema, Schema Registry).
Build harnesses with controlled test data and service virtualization so suites run consistently and can be repeated.
Design and build isolated, on-demand test environments on Linux and AWS:
Lifecycle: full service stacks (services, Kafka, databases) are created per branch or per run, start with seeded data and known state, and are torn down automatically.
Isolation: test runs don't interfere with each other or with shared environments.
Infrastructure: the environments are defined as code, with attention to cost.
Write data-validation tests across relational and analytical databases. Cover reconciliation and aggregation correctness.
Cover resilience and failure modes: broker and consumer outages, network partitions, timeouts, throttling, slow consumers and backpressure, reconnects, and authentication failures.
Own backend performance testing:
Latency and throughput: design and run load, stress, soak and spike tests on services, messaging pipelines, streaming and query APIs.
Baselines and regressions: set baselines and service-level targets (p50\/p99 latency, throughput, consumer lag), and catch regressions in CI.
Bottlenecks: profile them down to the CPU, GC, query or network layer.
Database queries: track query performance on analytical stores. Know how query shape and data volume drive response time.
Own backend test execution in CI\/CD: parallel runs, scheduled regressions, environment setup and teardown, and release quality gates.
Make failures diagnosable: structured logs, distributed traces (OpenTelemetry), correlation IDs across services, and clear reports.
Work with backend engineers, infrastructure, business analysts and traders to define and automate critical business workflows.
Use AI-assisted tools where they speed up writing tests and analysing failures.
Mandatory Skills Description:
5+ years of backend or service test automation, including framework design.
Strong Python (pytest, requests, asyncio, confluent-kafka or similar) for test frameworks, tooling and data validation.
Strong Java (JUnit 5, REST Assured, AssertJ, or similar) for testing JVM services.
Working TypeScript and Node.js skills: contributing to UI and cross-layer suites in the shared framework, and Node-based tooling (k6 scripts, Playwright API tests).
Hands-on Kafka experience: producing and consuming in tests, consumer groups, partitions and offsets, serialization and schema registry, and Kafka Streams or Connect.
Solid networking fundamentals: TCP\/IP, HTTP\/1.1 and HTTP\/2, WebSockets, TLS, DNS, load balancers, latency and packet loss. Able to debug with tcpdump\/Wireshark, curl and similar tools.
Strong SQL and database experience (PostgreSQL, SQL Server, or similar) for test data setup, verification and cleanup. Familiarity with columnar or analytical databases.
Hands-on performance and load testing:
Tools: k6, Gatling, JMeter or Locust, including Kafka throughput benchmarking.
Profiling: JVM tuning and profiling (GC, JFR, async-profiler) or Python profiling.
Analysis: reading latency distributions and percentiles correctly, including coordinated omission.
API, authentication and contract testing: OAuth\/JWT flows, payload and schema validation, and service virtualization (WireMock, MockServer, Hoverfly).
Experience building isolated test environments:
Linux: strong command-line skills, with shell scripting, systemd, processes, networking and performance troubleshooting.
Containers: Docker, Docker Compose and Testcontainers.
AWS: EC2, ECS or EKS, S3, IAM, VPC, MSK or RDS, and CloudWatch.
Infrastructure as code: Terraform, CloudFormation or CDK.
CI\/CD with Azure DevOps or Jenkins, and Git.
Strong reliability habits: isolated tests, controlled retries, failure-mode testing, and triage of flaky tests.
Clear communication and good documentation.
Nice-to-Have Skills Description:
Trading or buy-side experience: OMS\/EMS, the FIX protocol, market data, positions, allocations, or risk.
kdb+\/q, or other time-series databases used for tick data.
Contract testing with Pact. Property-based testing (jqwik, Hypothesis).
Kubernetes and Helm.
Chaos and fault-injection tools (Toxiproxy, Chaos Mesh).
Observability tools: OpenTelemetry, Grafana, Prometheus.
Experience with large-scale distributed systems.
Languages:
English: B2 Upper Intermediate<\/p>\n","protected":false},"excerpt":{"rendered":"
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