Quality Engineering Lead

Quick Facts

• Role: Quality Engineering Lead (National Scale & Data Integrity)

Description

Define and execute an end-to-end quality strategy for a greenfield, national-scale recycling platform connecting tens of thousands of IoT return machines, core systems, financial clearing networks, and data platforms.

Lead end-to-end data-flow validation across multiple partner vendors, focusing on data integrity, contract/schema testing, and automated quality gates. Stay hands-on with test automation, reconciliation, resilience/performance engineering, and AI-assisted engineering standards.

Responsibilities

• Define and defend verification strategy and establish automated quality gates across Azure DevOps/GitHub Actions pipelines.

• Lead an end-to-end data-flow validation team across partner vendors to automate data integrity checks and tracing of money/container flows across system hops.

• Act as primary technical point of contact to client leadership, aligning test strategies and SIT/UAT criteria through evidence and trade-off analysis.

• Implement consumer-driven contract testing and schema compatibility checks for REST APIs and event-driven architectures.

• Build data quality checks at ingestion and transformation stages; reconcile KPI/regulatory data products to source data using DataFrame-based validation.

• Design resilience, idempotency, fault injection, and load tests to ensure reliable handling of duplicates and dead-letter recovery.

• Establish AI-assisted engineering best practices (AI coding assistants and agent harnesses) with human oversight for quality definitions.

• Hire, mentor, and manage quality engineers; drive test code reviews and report quality metrics through completed flows and financial reconciliation.

Requirements

• 8+ years total Quality Engineering experience, including 2+ years leading QE teams on multi-vendor or complex platform engineering programs.

• Hands-on REST API testing experience, event-driven pipeline testing, and consumer-driven contract testing using Pact.

• Strong background in data platform validation with tools such as Great Expectations, pytest + chispa, Pandera, or dbt tests.

• Hands-on proficiency in Java and SQL (Python is a strong plus).

• Solid knowledge of major cloud services, with Azure preferred (API Management, Event Hubs, Service Bus, Functions).

• Deep experience configuring quality gates in Azure DevOps or GitHub Actions; daily use of AI coding assistants.

• Fluent English (C1+) with demonstrated ability to present strategies and negotiate with external vendors.

Benefits

• Opportunity to work on bleeding-edge projects

• Work with a highly motivated and dedicated team

• Competitive salary and flexible schedule

• Medical insurance

• Sports benefits

• Corporate social events

• Professional development opportunities

• Well-equipped office