Energy & Utilities | Data Engineer

Company Description

At Devoteam, we believe that good technology is imbued with strong human values and plays a key role in effecting positive change. Discover how Tech for People is unlocking the future, creating a favourable impact on individuals and the world at large. As a global powerhouse in Digital Transformation for premier organizations across EMEA, we boast a revenue of €652M. Our focus is on leveraging technology to create value for our clients, partners and employees in a world where tech is developed with people in mind. We take great pride in our collaborative culture, our dedicated staff working at the forefront of tech, and our diverse environment. After all, we are #TechforPeople. Join our eclectic team of Cloud Experts, Designers, Business Consultants, Security Specialists, Engineers, Developers, and myriad other skilled talents, situated in over 18 EMEA countries. Become one among our +8,000 tech and business leaders specializing in cloud, data, and cyber security. Let’s fuse technology with innovation and devise groundbreaking solutions that drive positive change.

Job Description

• Construction of data systems and pipelines;
• Analyzing and structuring raw data;
• Evaluating needs and objectives;
• Maintaining seamless operations of data pipelines;
• Conducting complex data analysis and examining results;  
• Preparing data for prescriptive and predictive modelling.

Qualifications

• Bachelor’s degree in IT or equivalent;
• Up to 6 years of professional experience;
• Proficiency in the methods and execution of architectural design surveys of analytical systems (database, database replicas, data lakes, and other storage systems, ETL, CDC, Spark transformations);
• Proficiency in the methods and design of a Data Efficiency program geared towards reducing data duplication, simplifying database replicas, streamlining processes that materialize data in intermediary steps, increasing the use of virtualization techniques, utilizing hot/cold/archive, methodologies for identifying unused data, automatic pruning, reducing the time series resolution in older periods;
• Experience in technically supporting data engineering and conceptual data modeling tasks.