Quality Engineering Lead

Grid Dynamics; Warszawa; On-site; PLN 120,000 - 180,000; Full time

Benefits offered by this job

Medical insurance

Flexible schedule

Professional development opportunities

Well-equipped office

Job summary

Grid Dynamics seeks a Quality Engineering Lead (National Scale & Data Integrity) to define and execute the quality strategy for a greenfield, national-scale platform. You will lead an E2E data-flow validation team and collaborate with client leadership, vendors, and architects while remaining hands-on with test automation and data integrity verification.

You will oversee verification strategy, data reconciliation, and contract testing across REST APIs and event-driven architectures, ensuring

Qualifications

• 8+ years in Quality Engineering, including 2+ years leading QE teams on multi-vendor/platform programs.
• Hands-on REST API testing, event-driven pipelines, and contract testing using Pact.
• Data platform validation using Python/Java frameworks and source-to-target reconciliation.
• Proficiency in Java and SQL; cloud services (Azure) knowledge.
• CI/CD pipelines and AI-assisted tooling experience.
• Fluent English with strong executive communication.

Responsibilities

• Define and defend verification approach for integrations and data platforms.
• Lead end-to-end data-flow validation across multiple partner vendors.
• Act as primary technical contact with client leadership and architects.
• Implement contract testing and schema checks for REST APIs and events.
• Build data quality checks at ingestion and transformation stages.
• Design resilience, fault injection, and load tests for high availability.
• Establish AI-driven QE practices with human oversight.
• Hire, mentor, and manage QE engineers and drive metrics.

Skills

QE leadership

REST API testing

Data pipeline validation

Java

SQL

CI/CD pipelines

AI-assisted tooling

Executive communication

Tools

Pact / PactFlow

Great Expectations

pytest

chispa

Pandera

dbt tests

Azure DevOps

GitHub Actions

Cursor

Claude Code

Codex

Microsoft Fabric

Job description

We are seeking a Quality Engineering Lead (National Scale & Data Integrity) to join a high-impact engineering team partnering with a Tier 1 UK Public Infrastructure & Environmental Organisation. In this role, you will define and execute the 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. You will lead an E2E data-flow validation team, acting as the primary point of contact for client leadership, partner vendors, and architects, while staying hands-on with test automation, contract testing, and data integrity verification.

Responsibilities

• Verification Strategy & Quality Gates: Define and defend the verification approach for the integration and data platforms, establishing robust automated quality gates across Azure DevOps/GitHub Actions pipelines.
• Cross-Vendor E2E Data Flow Validation: Lead the E2E data-flow validation team across multiple partner vendors to automate data integrity, tracing money and container flows across all system hops.
• Client & Stakeholder Leadership: Act as the primary technical point of contact and counterpart to the client's QE Lead, negotiating test strategies, quality gates, and SIT/UAT criteria with evidence and trade-off analysis.
• Contract & Schema Testing: Implement consumer-driven contract testing (Pact / PactFlow) and schema compatibility checks for REST APIs and event-driven architectures to prevent breaking changes.
• Data Platform Verification & Reconciliation: Build data quality checks at every ingestion and transformation stage, utilizing DataFrame-based validations (Great Expectations, chispa) to reconcile KPI and regulatory data products to source data.
• Resilience & Performance Engineering: Design resilience, idempotency, fault injection, and load tests to ensure high system availability, dead-letter recovery, and reliable handling of duplicate messaging.
• AI-Assisted Engineering Standards: Establish best practices for AI-driven software development (Cursor, Claude Code, Codex) and agent harnesses within the QE organization, ensuring human oversight for quality definitions.
• Team Leadership & Growth: Hire, mentor, and manage quality engineers across platform teams, driving test code reviews and reporting quality metrics through completed flows and financial reconciliation.

Requirements

• Professional QE Leadership: 8+ years of total experience in Quality Engineering, including 2+ years leading QE teams on multi-vendor or complex platform engineering programs.
• Contract & API Verification: Hands-on experience with REST API testing, event-driven pipelines, and consumer-driven contract testing using Pact (tests, provider verification, broker, can-i-deploy).
• Data Pipeline Quality: Strong background in data platform validation using Python/Java frameworks (e.g., Great Expectations, pytest + chispa, Pandera, or dbt tests) and source-to-target data reconciliation.
• Language & Tech Stack: Hands-on proficiency in Java and SQL (Python is a strong plus), with solid knowledge of major cloud services (Azure preferred: API Management, Event Hubs, Service Bus, Functions).
• CI/CD & AI-Assisted Tooling: Deep experience configuring quality gates in Azure DevOps or GitHub Actions, alongside daily usage of AI coding assistants (Cursor, Claude Code, or Codex).
• Executive Communication & Soft Skills: Fluent English (C1+) with proven capability to present complex quality strategies, negotiate with external vendors, and align cross-functional leadership.

Nice to have

• Azure & Data Platform Expertise: Direct hands-on experience with Azure managed services and Microsoft Fabric.
• Contract Testing Strategy: Practical experience with PactFlow bi-directional contract testing.
• Financial & Regulatory Domain: Domain experience in payments, financial settlement, container/unit-level reconciliation, or regulated public-sector platforms.
• Data Governance: Strong familiarity with data lineage, data quality controls, and compliance reporting.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment 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.