Data & Security Expert

V-IT NV; Brussel; Sur place; EUR 90 000 - 120 000; Plein temps

Résumé du poste

V-IT NV is seeking a Data & Security Expert in Brussels to lead data modelling, security governance, and analytics initiatives. Start ASAP with extension possibilities, collaborating with architecture, engineering, and business stakeholders to deliver robust data solutions.

The role covers data modelling, privacy considerations, access control, and cross-functional delivery. You will work with modern data platforms and drive secure, scalable data products across domains.

Qualifications

• Proficiency in SQL and data transformations.
• Experience building and validating data models across domains.
• Knowledge of data quality rules, lineage, and monitoring.
• Familiarity with cloud data platforms (Athena/Redshift/Snowflake).

Responsabilités

• Define conceptual, logical and implementable data model.
• Write and review SQL and transformation logic; validate results.
• Define data-quality rules, lineage and monitoring.
• Drive workshops with stakeholders across Sales, Marketing, and Engineering.
• Collaborate with Security/Privacy for governance and access controls.

Connaissances

SQL

ETL/ELT

Data modelling

Analytics

Data quality validation

BI tools

Outils

Athena

Redshift

Snowflake

Databricks

Synapse

Description du poste

For a client in Brussels we are looking for a Data & Security Expert.

Start ASAP, duration: to be agreed, extension possible

Data modelling and implementation

• Define the conceptual, logical and implementable data model.
• Identify source data, transformations, business rules, derived attributes, identity-linking requirements, historical needs and refresh expectations.
• Build, configure or guide the hands-on implementationaggregate and associated curated data products.
• Write and review SQL and transformation logic, validate results against source data and establish reproducible test cases.
• Define data-quality rules, reconciliation checks, exception handling, lineage and monitoring.
• Evaluate suitable implementation options with architecture and engineering teams. Keep the design technology-neutral until Athena, Redshift or another platform is formally selected.
• Ensure the model can evolve for new use cases and data sources without uncontrolled duplication or overengineering.

Security, privacy and consumer access

• Create and maintain a consumer-access matrix covering consumer, business purpose, permitted data, granularity, classification, environment, approval owner, retention conditions and technical enforcement.
• Define consumer categories, including application components, campaign or marketing processes, analysts, reporting solutions, recommendation services and authorised operational support roles.
• Apply least privilege, purpose limitation, data minimisation, segregation of duties and need-to-know principles.
• Determine when aggregation, masking, pseudonymisation, restricted views or other protective measures are required.
• Identify and assess risks created by combining customer profile, transaction, engagement, behavioural and health-related information.
• Define requirements for authentication, authorisation, encryption, audit logging, monitoring, access review and access revocation.
• Ensure that guidance and personalised-content use cases are clearly separated from commercial activation where their purposes, data or access conditions differ.
• Challenge unclear or excessive access requests and guide stakeholders toward a secure, workable alternative.
• Coordinate security and privacy reviews and document decisions, conditions, residual risks and accountable approvers.

Delivery and collaboration

• Drive workshops and decisions withSales & Marketing, domain stakeholders, Enterprise representatives, data owners, architecture, Security and Privacy.
• Maintain a prioritised backlog with dependencies, owners, decisions, risks, blockers and acceptance criteria.
• Escalate blockers early and propose concrete options with trade-offs and a recommended path.
• Support testing, business validation, release readiness, documentation, knowledge transfer and operational handover.
• Establish reusable patterns for onboarding new data, adding new attributes and authorising new consumers.

Data engineering and analytics

• Advanced SQL and hands-on experience with ETL/ELT, data transformation, analytical modelling and data-quality validation.
• Experience with dimensional and entity-oriented modelling, metadata, lineage and historical data patterns.
• Experience integrating data from multiple business domains into a coherent customer view.
• Ability to assess platform options based on security, performance, scalability, cost, operability and integration requirements.
• Experience with one or more common analytical technologies such as Athena, Redshift, Snowflake, Databricks, Synapse or comparable platforms. No specific technology is mandatory at this stage.
• Experience with BI, recommendation, campaign or content-personalisation consumers is an asset.

Security, privacy and governance

• Deep knowledge of analytical-data access control, least privilege, RBAC/ABAC patterns, purpose-based access and segregation of duties.
• Experience with data classification, data minimisation, masking or pseudonymisation, retention, secure sharing and access reviews.
• Ability to turn policies and business purposes into enforceable permissions at dataset, view, row, column or attribute level, depending on the selected technology.
• Knowledge of encryption, identity and access management, audit logging, security monitoring and incident traceability.
• Experience assessing aggregation, inference, misuse, secondary-use, re-identification and excessive-access risks.
• Ability to work effectively with Security, Privacy, Legal, architecture, data owners and business stakeholders.