Harmoniz - The Art of Seed Innovation is a global agtech company specializing in breeding greenhouse seeds. . The company is focused on developing innovative, great-tasting, and virus-resistant tomatoes, expanding into pepper and cucumber seed development.

Main Role Purpose: 

Own and elevate the quality of our data (first priority) and UI (second) across a greenfield AI‑driven Agri‑Tech platform. You will help maintain environment separation and health (dev/stage/prod), create manual and automated tests for data quality/integrity and UI, participate in CI/CD quality gates, and support the dev teams as needed. You will play an active role in defining Quality requirements, writing acceptance criteria, and aligning test planning with sprint progress and deployments.

Responsibilities:

Data Quality (primary):

o   Define and implement data quality criteria: schema/contract checks, null/unique constraints, ranges, referential integrity, completeness/freshness, duplicates, reconciliation vs. golden datasets, and drift/anomaly detection.

o   Automate data checks with Python/SQL (e.g., pytest + SQL assertions; Great Expectations/Deequ‑style validations); publish results and trends to dashboards.

o   Integrate data tests into CI/CD as quality gates; fail builds on contract breaks or regressions.

o   Manage safe test data: synthetic datasets, seed scripts, masking/PII hygiene, and versioned fixtures.

UI Quality (secondary):

o   Author test plans and manual charters for new features; convert high‑value paths into automation (e.g., Playwright/Cypress).

o   Validate responsive/adaptive behavior (desktop–tablet–mobile), cross‑browser basics, accessibility checks (WCAG essentials).

o   Coordinate with Full‑Stack on UX acceptance criteria and regression suites for complex visualizations and heavy data views.

API / Service Quality:

o   Create API tests (REST/GraphQL/GraphAPI) with contract checks (e.g., PACT‑style), schema evolution tests, pagination & performance smoke.

o   Add basic load/smoke scenarios (k6/Locust‑style) for critical endpoints.

Environment Separation & Health:

o   Help keep dev / stage / prod cleanly separated; monitor environment health; maintain reset scripts, seed data, and ephemeral preview environments where applicable.

o   Validate serverless‑first deployments (Functions/Lambda, event‑driven flows), queues/topics, and scheduled jobs.

CI/CD & Release Quality:

o   Co‑design and maintain CI/CD checks with the team: staged pipelines, artifacts, test coverage thresholds, lint/format/security scans, and post‑deploy smoke.

o   Support canary/shadow checks and rollback signals; maintain quality runbooks.

o   Align test plans to sprint goals and release timelines; update the Definition of Done with quality criteria.

Collaboration & Support:

o   Work closely with Data Engineering (data Control Tower checks, lineage/metadata signals), Data Science (evaluation sets, basic LLM/RAG sanity checks like groundedness/hallucination rate), and Full‑Stack (UI flows, error handling).

o   Document test plans, cases, and issue reproduction steps; participate in SCRUM rituals and rare “all‑hands‑on‑deck” incidents.

Qualifications:

• 0–3 years QA/automation experience (or strong internship / projects).
• BA with relevant professional education 
• Python for test automation (e.g., pytest), basic TypeScript/JavaScript for UI tests, and SQL for data validation.
• Familiarity with data‑quality frameworks (Great Expectations/Deequ concepts), UI automation (Playwright/Cypress), API testing (Postman/Newman), and contract testing (PACT‑style).
• Understanding of CI/CD and modern deployment strategies with an emphasis on a serverless‑first approach (Functions/Lambda, managed orchestration, event‑driven services); practical fluency in containers (Docker, Kubernetes/EKS/AKS) where needed.
• Basics of Azure or AWS, Git workflows, issue tracking, and SCRUM ceremonies.
• Strong attention to detail, structured test writing, clear communication; fluent Hebrew and English.