QC Team Lead

greehill

. Lead and develop the three-person QC function, including workload planning, prioritization and performance management .

Posted 10/21/2026contractBudapest • HungarySeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading Quality Control processes, implementing automated quality checks, and analyzing data to improve quality outcomes. Proficient in managing teams, developing quality standards, and utilizing AI and machine learning for quality assurance.

Highest-signal resume keywords

Quality Control LeadershipAutomated QC ImplementationData Analysis with SQL or PythonKPI Development and ReportingAI and Machine Learning Application

ATS Keywords

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Hard Skills

Quality ControlQuality AssuranceData QualityOperations ManagementAutomated WorkflowsSOP DevelopmentData AnalysisRoot-Cause AnalysisQuality StandardsPerformance Management

Soft Skills

Strong CommunicationTeam ManagementCoaching and TrainingPrioritizationCross-Functional Collaboration

Tools & Technologies

SQLPythonAI-Native QC SystemsQuality DashboardsData-Quality Tools

Industry Keywords

Geospatial DataGISLiDARPhotogrammetryRemote SensingHuman-in-the-Loop AIConfidence-Based Review Workflows

Tech Stack

Tools & technologies

PythonRemote SensingSQL

About the role

Key responsibilities & impact

Lead and develop the three-person QC function, including workload planning, prioritization and performance management
Define daily and weekly QC priorities based on project deadlines, production capacity and quality risk
Train and coach QC specialists and build resilience through cross-training and documented working practices
Ensure complaints, QC findings and production issues are handled through one consistent quality process
Maintain consistent QC practices across locations, projects and production teams
Own the end-to-end QC process for data-production workflows
Design and implement an AI-native QC system embedded in the production flow
Define automated checks, sampling strategies, acceptance criteria, quality thresholds, quality gates and escalation procedures
Use risk-based sampling to focus human review on high-risk and ambiguous cases
Work with ML and Engineering teams to improve validation rules, issue detection and automated quality checks
Establish and maintain QC KPIs, quality dashboards and a consistent defect taxonomy
Track error rates, escaped defects, client complaints, completeness, accuracy, rework, rejection rates, review time and automation coverage
Analyze QC results to identify trends, root causes and systemic problems
Develop and maintain QC SOPs, checklists, quality standards and corrective-action processes
Turn QC findings and client complaints into structured feedback for Production, ML, Product and Engineering
Lead root-cause analysis and corrective and preventive actions for recurring quality problems
Reduce repetitive manual inspection while maintaining or improving quality
Support project teams in defining project-specific quality requirements
Monitor quality throughout high-priority projects and flag risks early
Provide final QC input before project delivery and ensure lessons learned improve future workflows

Requirements

What you’ll need

3+ years of experience in Quality Control, Quality Assurance, Data Quality, Operations or a related field
Proven experience leading a small QC, QA, data-quality or operations team
Experience working as a hands-on lead who combines people management with individual delivery
Demonstrated success improving measurable quality outcomes in a production environment
Experience designing or implementing automated QC, data-validation or exception-handling workflows
Practical experience analyzing data with SQL, Python or comparable tools
Experience working with large datasets and identifying patterns in quality issues
Experience creating and improving SOPs, quality standards and operational processes
Experience investigating systemic defects and implementing corrective and preventive actions
Ability to prioritize quality issues based on business and client impact
Strong communication skills and ability to work across technical and operational teams
Professional English communication skills
Experience applying AI or machine-learning methods to anomaly detection, classification, prioritization or quality review is valued
Experience with human-in-the-loop AI or confidence-based review workflows is valued
Experience with geospatial data, GIS, LiDAR, photogrammetry or remote sensing is valued
Experience working with distributed or outsourced production teams is valued
Experience with data-quality dashboards and KPI reporting is valued

Benefits

Comp & perks

Opportunity to join a dynamically growing startup team
Possibility to work and learn in an international, open-minded team of passionate (green-)tech experts
Ownership and impact
Exposure to cutting-edge AI and LiDAR technology
Contribution to urban sustainability and climate resilience