AI/ML Data Engineer: Build Scalable Pipelines & Data Quality

Aptiv; Kraków; On-site; PLN 120,000 - 180,000; Full time

Job summary

Aptiv Kraków is seeking a data science professional to design and implement robust data extraction, transformation, and loading solutions for AI/ML data platforms. You will develop data quality metrics, APIs, and data pipelines to support complex processing needs, while enriching data for analytics and research.

The role requires collaboration in cross-functional teams and ongoing professional development. The ideal candidate holds a science or engineering degree, demonstrates initiative and

Qualifications

• Degree in Data Science, Robotics, Computer Science or related field.
• High motivation, integrity and initiative.
• Creativity, transparency and passion for excellence.
• Methodical problem solving approach.
• Advanced presentation and communication skills in English.
• Honesty with company, clients and co-operating partners.

Responsibilities

• Design and implement data extraction, transformation and loading solutions.
• Design data quality metrics.
• Implement APIs and organize raw/processed data.
• Build data pipelines and processing tools to meet requirements.
• Apply data enrichment/analysis in AI/ML data platforms.
• Research and develop big data technologies.
• Monitor performance of innovations via trials.
• Optimize technical solutions across multiple criteria.
• Prepare technical and scientific documentation.
• Collaborate in project meetings and continuous learning.

Skills

Data science

Problem solving

English communication

Education

BSc or MSc in Data Science

Related field in Computer Science/Robotics

Tools

Python

ETL

APIs

Job description

Aptiv Kraków is seeking a data science professional to design and implement robust data extraction, transformation, and loading solutions for AI/ML data platforms. You will develop data quality metrics, APIs, and data pipelines to support complex processing needs, while enriching data for analytics and research.

The role requires collaboration in cross-functional teams and ongoing professional development. The ideal candidate holds a science or engineering degree, demonstrates initiative and