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Introduction
Railways for the world of tomorrow.
Responsibilities

DB Engineering & Consulting (DB E&C) is a part of the DB group, a world leading global railway company with an extensive organization in Germany and projects around the world. Our company offers technically sophisticated and customized infrastructure, mobility and transport solutions. With our sustainable concepts, gained from our experience in project work for decades, we ensure the future success of economic regions, make important contributions to the protection of the environment and help shape the world of the future. We have 180 years of rail experience, and our infrastructure projects connect continents. We set the standard for transportation and modern mobility.


We are seeking a Data Engineer / Data Scientist as part of our DB Engineering & Consulting GmbH Branch Office. The job opening is located in the Middle East and offers exciting challenges and potential for career growth.



Responsibilities:

  • Support our Asset Condition Assessment initiatives. 
  • Responsible for designing data pipelines, analyzing asset performance data, developing predictive models, and delivering actionable insights to improve asset reliability, lifecycle management, and maintenance strategies.
  • Role bridges data engineering and advanced analytics, working closely with engineering, operations, and asset management teams.
  • Design, build, and maintain scalable data pipelines for asset condition monitoring systems.
  • Integrate data from multiple sources (IoT sensors, Maximo, SCADA systems, CMMS, ERP, inspection reports, etc.).
  • Ensure data quality, validation, cleansing, and governance standards.
  • Develop data models and optimize storage solutions (SQL/NoSQL databases, data lakes, cloud platforms).
  • Automate ETL/ELT processes and workflows.
  • Perform exploratory data analysis (EDA) on asset condition and performance datasets.
  • Develop predictive and prescriptive models for: Failure prediction, Remaining Useful Life (RUL) estimation, Risk-based maintenance and Anomaly detection
  • Implement machine learning algorithms and statistical models.
  • Validate models and monitor performance over time.
  • Translate analytical findings into clear, actionable insights.
  • Work with asset managers, reliability engineers, and maintenance teams to understand business needs.
  • Develop dashboards and visualizations (Power BI, Tableau, Python, etc.).
  • Present insights and recommendations to technical and non-technical stakeholders.
  • Document methodologies, data pipelines, and models.
Qualifications
Qualifications:

  • Bachelor’s or master’s degree in data science, Computer Science, Engineering, Statistics, or related field. 
  • At least 10 years’ experience in data engineering, data science reliability engineering, asset condition assessment, deterioration modelling and performance analysis. 
  • Experience in Asset Management systems (Maximo, SCADA). 
  • Knowledge of machine learning techniques and statistical modeling. 
  • Strong background in Data Integration and performance modelling expertise. 
  • Professional certification is advantage. 
  • Qatar/GCC working experience is an Advantage. 
  • Experience working with Ministry, Government Agencies, and Entities.  
  • Proficiency in English, both spoken and written. Arabic speaker is an advantage. 
  • Full Computer Literacy, PowerPoint, AUTOCAD, understanding on GIS Software. 
  • Excellent communication skills are essential to success in this role.
  • Driving license is required to drive to site or to technical meetings with the client representative.
Disclaimer
In case you match the profile and are interested in a complex task within the transport sector, we are looking forward to receiving your application.

Please state your earliest possible availability as well as your salary expectations.

Please note that your application will be saved and used in electronic form as a part of the application process for this position.

Thank you for considering DB Engineering & Consulting as prospective employer!