Data Engineer Expert (InformationTechnology / Software)

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.