Quality Engineering Lead

Grid Dynamics is a technology consulting company specializing in platform and product engineering, AI, and advanced analytics services. The company works with enterprise clients undergoing business transformation, offering expertise in data, analytics, cloud & DevOps, application modernization, and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

• 8+ years of experience in Quality Engineering with 2+ years leading QE teams in complex, multi-vendor platform projects.
• Hands-on experience with REST API testing, event-driven pipelines, and consumer-driven contract testing using Pact.
• Strong background in data platform validation using Python/Java frameworks (e.g., Great Expectations, chispa, Pandera).
• Proficiency in Java and SQL, with knowledge of cloud services, preferably Azure (API Management, Event Hubs, Service Bus, Functions).
• Experience configuring quality gates in Azure DevOps or GitHub Actions and daily use of AI coding assistants (Cursor, Claude Code, Codex).
• Fluent English communication skills (C1+) with ability to present quality strategies and negotiate with vendors.

Nice to have:

• Direct hands-on experience with Azure managed services and Microsoft Fabric.
• Practical experience with PactFlow bi-directional contract testing.
• Domain experience in payments, financial settlement, or regulated public-sector platforms.
• Familiarity with data lineage, data quality controls, and compliance reporting.

• Define and defend the verification strategy and automated quality gates across Azure DevOps/GitHub Actions pipelines.
• Lead the end-to-end data-flow validation team across multiple partner vendors to automate data integrity.
• Act as the primary technical contact for the client's QE Lead and stakeholders, negotiating test strategies and quality gates.
• Implement consumer-driven contract testing and schema compatibility checks for REST APIs and event-driven architectures.
• Build data quality checks and perform source-to-target reconciliation in data platforms using DataFrame-based validations.
• Design resilience, fault injection, load tests to ensure system availability and reliable messaging handling.
• Establish AI-assisted engineering best practices within the QE organization, ensuring human oversight.
• Hire, mentor, and manage quality engineers, driving test code reviews and reporting quality metrics.

INFORMATION ON PERSONAL DATA PROCESSING: Your personal data will be processed by Grid Dynamics Group entities as co-administrators. Provision of personal data is voluntary but required to participate in recruitment. Data may be transferred outside the EU under intra-group agreements. You have rights under GDPR including access, correction, deletion, and objection. Complaints can be filed with the Personal Data Protection Office in Warsaw.