Data Engineer (GCP)

Addepto is a leading AI consulting and data engineering company that builds scalable, ROI-focused AI solutions for large enterprises and startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. The company focuses exclusively on Artificial Intelligence and Big Data, helping organizations unlock the potential of their data through systems designed for measurable business impact and long-term growth. Addepto has developed its own product, ContextClue, and contributes open-source solutions to the AI community. It is part of KMS Technology, a US-based global technology group, combining AI specialization with enterprise-scale delivery capabilities.

• At least 3 years of commercial experience in Data Engineering, AI analytics, or cloud-based AI/ML solutions
• Strong programming skills in Python, including clean code practices and OOP design
• Hands-on experience with GCP services, especially BigQuery
• Experience working with Machine Learning models and large-scale datasets
• Experience in collecting and analyzing LLM token usage data, including forecasting and anomaly detection use cases
• Familiarity with cloud-based analytics and scalable data processing solutions
• Understanding of LLMs and AI/ML systems in production environments
• Excellent communication skills and experience working directly with clients and business stakeholders
• Ability to work independently and take ownership of project deliverables
• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or a related field
• Good English communication skills (C1 level)

Nice to have:

• CI/CD
• Kubernetes
• Power BI
• Airflow

• Design, develop, and maintain scalable data pipelines and analytics solutions in GCP
• Develop solutions for collecting, processing, and analyzing LLM token usage data
• Build forecasting and anomaly detection mechanisms to monitor AI consumption patterns
• Optimize and maintain BigQuery datasets and cloud-based processing environments
• Collaborate with cross-functional teams to translate business needs into scalable AI/data solutions
• Ensure high-quality data processing through testing, monitoring, and automation best practices
• Contribute to data architecture, analytics frameworks, and continuous improvement initiatives