Senior Data Engineer

Location: Budapest, Budapest, Hungary

Department: MPS PRS

Workplace: hybrid

Employment Type: full

Description

Our client is a stable, privately owned IT consulting company with over 20 years of experience delivering enterprise-scale technology projects across multiple industries. Their long-standing partnerships with large organizations reflect both technical credibility and financial stability, supported by consistently strong external credit ratings. The company operates with a lean core team, low turnover, and a collaborative, trust-based culture focused on long-term cooperation and high-quality delivery. They work across diverse domains including telecommunications, healthcare, and academia, offering engineers the opportunity to contribute to varied, complex initiatives while maintaining a flexible and supportive work environment.

We are looking for a Senior Data Engineer to work on large-scale data environments involving high-volume datasets, complex integrations, and analytical use cases. This is a hands-on engineering role focused on building and maintaining data pipelines, understanding end-to-end data flows, and troubleshooting data quality issues across distributed systems.

You will work closely with engineers, analysts, and stakeholders to ensure reliable, scalable, and well-structured data solutions that support analytics and machine learning initiatives.

Tasks:

• Design, build, and maintain scalable data ingestion and ETL/ELT pipelines
• Work with large datasets and interfaces feeding enterprise-scale databases
• Analyze data flows and troubleshoot inconsistencies across systems
• Perform root cause analysis to trace incorrect outputs back to source systems
• Prepare datasets for analytical and machine learning use cases
• Contribute to data modeling and data mapping activities
• Support ML initiatives through data preparation, evaluation, and optimization
• Define and implement data quality monitoring frameworks
• Develop visualizations to support data interpretation and insights

Requirements

• Solid experience in data engineering or closely related backend/data roles
• Strong hands-on experience with Python
• Experience with Scala or Java is a strong advantage
• Proven background working with large datasets and distributed systems
• Experience with ETL/ELT pipelines and data integration solutions
• Familiarity with Kafka or other streaming technologies is a plus
• Understanding of data modeling, data mapping, and data lineage
• Knowledge of statistics and applied mathematics
• Exposure to machine learning workflows and model lifecycle concepts
• Strong analytical mindset and structured troubleshooting approach
• Systems thinking and ability to work independently

Benefits

• Long-term, stable projects
• Flexible hybrid working model
• Fully flexible working hours
• Diverse projects and technology exposure
• Supportive team culture
• Training and professional development support
• Flat structure and collaborative environment