Job Description

Role Summary

Lytx powers real-time safety for thousands of companies worldwide. The Data Services team provides shared capabilities—Schema Registry and data contracts, Data Product Catalog, Data Quality and Observability frameworks, and Data Delivery/Subscriptions—that many products rely on. As a Software Engineer in Test, you will ensure these multi-tenant services are correct, reliable, and measurable before they reach production.

You will own service test infrastructure, API and contract tests, automated data quality signals, and performance/resilience suites. Working closely with software engineers, you’ll read and review service code, design testability into solutions, and enforce CI quality gates so safety insights ship with confidence.

Responsibilities

Design and implement test infrastructure and harnesses for backend services (Reporting Services, Registry, Catalog, DQ/Observability, Delivery).
Define and automate data contract tests with versioning and compatibility checks.
Build automated data quality checks and service observability; verify signals are emitted and actionable.
Create performance/resilience suites (latency, throughput, error handling) and block releases on regressions.
Integrate CI quality gates (GitHub Actions/Jenkins) for tests, coverage, and reliability signals.
Read, review, and collaborate on service code; contribute fixes to improve testability.
Partner with Enablement and Pipeline teams on shared testing patterns and DQ frameworks.
Document test strategies, playbooks, and templates; coach teams via office hours and reviews.
Design effective test cases across unit, integration, system, and contract testing; document test conditions, data setup, and expected outcomes.

Required Qualifications

5+ years as a software/test engineer validating backend and data services with strong coding skills.
Proficiency with Python and one typed language (C# preferred); strong SQL.
API testing (REST/gRPC/event-driven) and consumer-driven contract testing.
Kafka familiarity and event-driven patterns; basic understanding of lakehouse formats and metadata/catalog.
CI/CD experience with quality gates; property-based testing and test doubles.
Solid engineering fundamentals: concurrency, performance profiling, test design, and code reviews.

Preferred Qualifications

Data testing frameworks (Great Expectations/dbt tests) and observability tooling.
Experience with Schema Registry (Apicurio) and metadata/catalog systems (OpenMetadata); lineage tooling.
Performance tools (JMeter/Locust) and custom service perf harnesses; chaos testing.
Kubernetes and IaC (Terraform/Helm)