Data Engineer

About the role

The Machine Learning Team at Smartex is dedicated to transforming the textile industry with AI‑driven inspection solutions. We are seeking a motivated Data Engineer to design, build, and enhance the data infrastructure that powers our inspection products, including Python backend services, processing pipelines, and dashboards.

Key responsibilities

• Build and maintain pipelines for collecting, validating, processing, and organizing data used by the Machine Learning team.
• Develop Python backend services, APIs, and internal tools to improve data collection, labeling, review, and dataset preparation.
• Create dashboards and reports that visualise dataset coverage, labeling progress, quality metrics and operational bottlenecks.
• Translate product and ML requirements into practical data workflows and coordinate dependencies across teams.
• Collaborate with ML engineers and textile experts to define defect categories, labeling guidelines and implement them in data workflows.
• Document processes, write readable, tested code and share ownership across the team.

Required profile

• At least 4 years of professional experience in data engineering, Python backend development or a related software role.
• Strong practical Python skills for building services, automation and data‑processing tools.
• Confidence with SQL, relational databases and data modelling.
• Proven experience designing data pipelines that handle incomplete or changing data.
• Experience building dashboards or reports that support team decision‑making.
• Ability to coordinate work across colleagues, mentor others and take ownership of delivery.
• Proficiency with Git and solid software development practices, including testing and documentation.
• Clear communication with both technical and non‑technical stakeholders, fluency in English.

Required skills

• Python
• SQL
• Relational databases
• Data modelling
• Data pipeline development
• Dashboard creation
• Git
• Software testing and documentation

What we offer

• Career progression opportunities
• Employee stock options
• Diverse and talented team in a fast‑paced environment
• Impactful work that contributes to a more sustainable textile industry
• Hybrid work model
• Collaboration with senior management