Data Engineer Expert

Our client, a leading Software, Information and Communication Technologies company, operates internationally (Athens, Brussels, Luxembourg, Copenhagen, Stockholm, London, Nicosia, Hong-Kong, Valetta, etc). Our client is a renowned supplier of IT services to government institutions, multinational corporations, public administrations and multinational companies, research and academic institutes.

 

Role Overview

Our client currently has a vacancy for a Data Engineer Expert fluent in English, to offer his/her services as an expert who will be based in Luxembourg. The work will be carried out either in the company’s premises or on site at customer premises. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team on site.

Job type: Full time/Permanent

Location: Luxembourg

Workplace: Onsite

Please note that we can consider only EU candidates for this position due to security clearance.

Requirements

• University degree in Data Science or relevant discipline, combined with minimum 10 years of relevant working experience in IT;
• At least 10 years of experience with relational and analytical databases, including Microsoft SQL Server, Oracle, PostgreSQL, and Amazon Redshift;
• At least 10 years of experience in SQL / SQL-PL for data querying, transformation, and optimisation.
• At least 10 years of experience in the use of the Microsoft Office Suite (Word, Excel, PowerPoint);
• At least 7 years of experience leading Business Intelligence (BI) development initiatives;
• At least 7 years of experience in the design and implementation of data marts;
• At least 7 years of experience implementing database synchronisation tools developed in PL/SQL for Oracle;
• At least 5 years of experience with cloud-based data integration and analytics solutions on Microsoft Azure, including Azure Data Factory, Azure Synapse Pipelines and/or Fabric, Azure Synapse Analytics, Azure Data Warehouse, Azure Synapse Apache Spark Pools, Azure Data Lake Storage Gen2, and Azure Stream Analytics;
• At least 5 years of experience with Microsoft Power BI, including data modelling using M and calculations using DAX;
• At least 5 years of experience using Python, particularly notebooks for data analysis and processing;
• At least 4 years of experience with ETL and analytical solutions, including Microsoft SSIS and SSAS (multidimensional and tabular);
• At least 4 years of experience in Azure Data Warehouse (DWH) implementation;
• At least 4 years of hands-on experience with Microsoft SQL Server Management Studio (SSMS) and Oracle Developer;
• At least 2 years of experience with enterprise reporting and analytics tools, such as Qlik Sense, Tableau, and SQL Server Analysis Services (SSAS);
• At least 2 years of experience working with Confluence and JIRA in agile or structured project environments;
• At least 1 year of experience with network topology concepts, including TCP/IP, load balancers and proxy servers;
• At least 1 year of experience applying Business Intelligence solutions to process-driven applications;
• Excellent command of the English language.

Responsibilities

• Provide technical consultancy for Data Engineering initiatives across multiple projects;
• Lead and contribute to Business Intelligence (BI) implementation projects on Microsoft Azure, ensuring robust and scalable solutions;
• Analyse, design, and implement cloud-based data architectures, including data ingestion, storage, processing, and security components on Azure;
• Manage, monitor, and optimise data ingestion pipelines, data storage solutions, and data processing workflows;
• Develop and maintain data platforms, ensuring data quality, security, and regulatory adherence;
• Draft, review, and maintain technical, functional, and non-functional specifications in close collaboration with Enterprise Architecture and Operations teams;
• Actively participate in technical working groups and project meetings, collaborating with developers, project teams, stakeholders, and both technical and non-technical users;
• Communicate complex technical concepts clearly to non-expert audiences, supporting alignment between business and technical teams.