Data Quality Coordinator

About the role

This position centers on managing and refining the processes used to generate high-quality training data for robotics systems. You will act as the primary link between engineering departments and data collection staff to ensure that technical needs are met with precise operational standards. In this role, you will own the definition and execution of data quality workflows that directly influence model accuracy and reliability. You will establish the operational discipline required to transform raw robotic interactions into structured, reliable datasets. Your work will ensure that every dataset released to engineering teams meets strict standards for clarity, completeness, and consistency. You will drive continuous improvement by analyzing bottlenecks and standardizing procedures across collection cycles. This position is critical for aligning technical objectives with on-ground execution to maintain a high-trust feedback loop between teams.

Key facts

What you'll do

• Partner with development teams to establish data collection criteria that improve model performance.
• Convert technical specifications into actionable quality standards and Standard Operating Procedures.
• Create and manage version-controlled documentation for data collection workflows.
• Design and conduct training sessions for operators to ensure consistent task execution.
• Audit collected data and evaluate operator performance to spot deviations and areas for growth.
• Track quality metrics and operator consistency to boost acceptance rates.
• Assist engineers in refining quality requirements and building automated validation tools.
• Lead process improvement initiatives by gathering feedback and implementing operational best practices.
• Define clear metrics for data accuracy and completeness to guide collection efforts.
• Liaise with cross-functional stakeholders to align data strategies with product roadmaps.
• Monitor real-time data streams to identify anomalies and trigger corrective actions.
• Standardize labeling guidelines to reduce ambiguity and rework across teams.
• Facilitate root cause analysis for data issues and document resolutions for future prevention.
• Support the rollout of new data collection tools with structured onboarding and validation checks.

Requirements

• Bachelor degree in Robotics, Engineering, Computer Science, Industrial Engineering, Quality Management, or a related field.
• Background in technical operations, quality assurance, or structured operational processes.
• Ability to analyze quality issues and propose effective process changes.
• Proven skill in organizing workflows and drafting standardized documentation.
• Strong communication abilities for working between technical and operational groups.
• Experience in coordinating training programs or operational procedures.
• Capacity to work methodically in a fast-paced environment with evolving priorities.
• Willingness to follow documented procedures and contribute to their enhancement.
• Commitment to maintaining data integrity across all stages of the collection pipeline.
• Understanding of quality management principles and their application in operational contexts.
• Familiarity with standard operating procedures and their role in scaling operations.
• Willingness to adhere to company policies and support compliance objectives.
• Openness to feedback and collaboration within a structured team environment.
• Focus on accuracy and attention to detail in all documentation and review tasks.

Nice to have

• Prior work with AI, machine learning, or robotics data collection.
• Experience creating work instructions or quality documentation.
• Background in training technical staff or operators.
• Familiarity with dataset quality management or data annotation.
• Knowledge of robot learning pipelines and robotics workflows.

Practical notes

• Employees receive a corporate benefits program providing 100 Euro net per month for health, mobility, and learning.
• The office features a rooftop terrace, free drinks, and fruit.
• Agile Robots is an international company with over 2300 employees globally.
• The company supports diversity and encourages applications from all backgrounds.
• The position is based in Munich, Germany, at the company headquarters.
• This is a full-time, permanent engagement requiring on-site presence.
• No travel is required for this role as the position is anchored at the central facility.
• The work schedule follows standard local business hours in alignment with corporate policy.
• Candidates must be legally authorized to work in Germany without sponsorship restrictions.
• The application process will include a review of documentation and possible assessments.
• Early submission is recommended to ensure full consideration within active hiring cycles.
• Only candidates matching the outlined requirements will be contacted for further steps.

This role is essential to maintaining the operational excellence that supports Agile Robots global ambitions. By focusing on process rigor and clear communication, the Data Quality Coordinator ensures that the company's data foundation remains solid and scalable. The successful candidate will thrive in an environment where precision, collaboration, and continuous learning are highly valued. You will contribute directly to the reliability of robotic systems by ensuring that the data they learn from is trustworthy and consistent. This position offers the opportunity to shape data practices at the intersection of technology and operations. The work environment encourages structured thinking, ownership, and proactive problem solving. You will work alongside engineers, operators, and managers to uphold the highest standards of data integrity. The role provides a clear line of impact from daily tasks to strategic data quality outcomes. If you are detail-oriented, process-driven, and passionate about operational excellence, this position aligns with your professional goals. Joining Agile Robots at this stage offers the chance to help define practices that scale across a growing international organization.