Our client is looking for a Data Pipeline Analyst
Description
The assignment combines data analysis, semantic modelling (linked data), understanding of data pipelines and the management of small-scale data projects, in close collaboration with business stakeholders, Data & Digital and ICT.
a. Scoping and steering of data projects
Identify and analyse the needs of operational stakeholders in terms of data, analyses and semantic structuring of information. Define the scope, objectives, deliverables and planning of small to medium-sized data projects (data pipelines, analyses, light automations), integrating principles of data reuse and interoperability. Monitor progress, ensure functional coordination of the parties involved and communicate clearly to stakeholders. Ensure compliance with scope, deadlines and quality of deliverables.
b. Analysis of data, data pipelines and semantic models
Analyse existing data flows, their sources, transformations and associated data models. Design, analyse and evolve semantic data models (linked data – RDF, OWL) to ensure data consistency, interoperability and reusability. Identify improvement opportunities in terms of data quality, reliability, performance and reusability. Contribute to the definition or optimisation of data pipelines in collaboration with ICT and Data teams.
c. Production of analyses and analytical deliverables
Carry out data analyses supporting concrete operational use cases. Develop reports, performance indicators (KPIs) and dashboards adapted to operational users. Validate the relevance and usability of results with stakeholders.
d. Coordination and transversal collaboration
Act as a functional interface between business, Data & Digital and ICT. Facilitate workshops, clarify needs and support decision-making. Contribute to the alignment of data initiatives with the Data & Digital roadmap and existing standards.
e. Documentation and knowledge transfer
Document analyses, functional choices, semantic data models and deliverables using architecture tools such as SPARX Enterprise Architect. Formalise best practices related to data analysis, semantic modelling and the use of data pipelines. Provide knowledge transfer to internal teams to strengthen their autonomy.
Technical skills
- Scoping and steering of data projects: ability to define scope, objectives, deliverables and coordinate stakeholders for small-scale data projects (L3: at least 5 years of experience).
- Data analysis: ability to analyse datasets and produce actionable insights for operational use cases (L3: at least 5 years of experience).
- Understanding of data pipelines: functional understanding of data flows, from data source to analytical exploitation (L3: at least 5 years of experience).
- Practical experience with linked data technologies, including RDF and OWL, and semantic data modelling in data integration or data pipeline contexts (L2: at least 2 years of experience).
- SQL: extraction, transformation and analysis of data across multiple systems (L2: at least 2 years of experience).
- Reporting and visualisation: ability to produce reports, indicators (KPIs) and dashboards understandable to operational users (L2: at least 2 years of experience).
- Practical experience with SPARX Enterprise Architect for modelling data structures, data flows and architectures, and for structured and maintainable documentation of data solutions (L2: at least 2 years of experience).
- Language 1: French or Dutch (C1: complex mastery).
- Language 2 (other than Language 1): French or Dutch (understanding) (B1: intermediate level).
Soft skills
- The candidate must demonstrate knowledge of the company, the IT world, and understand the challenges of the requested role, as well as the mission and key activities of the company.
- The candidate must demonstrate the ability to integrate into the company teams, particularly through the values of kindness, courage, positivity and reliability.
- The candidate must demonstrate role‑related skills in line with the ICT department, including presentation skills, a professional attitude, correctness and respect for management, clear and effective communication, and responsible commitment for the duration of the contract.
