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Visible on IKONS todayNewPopular
BrusselsHybridHours negotiable<3months
As a Data Quality Developer, you will play a key role in strengthening enterprise data quality across multiple business domains. You will develop robust data quality controls, support large-scale IT and migration projects, and implement automated reconciliation processes that improve data reliability and business decision-making.
Working with modern data technologies and best practices, you will contribute to enterprise-wide data governance while ensuring high-performance, scalable, and maintainable data quality solutions.
What you do
- Design, develop, and maintain enterprise data quality solutions
- Build automated data quality checks using Python and Apache Spark
- Translate business requirements into scalable technical solutions
- Estimate development effort and technical feasibility for new requests
- Apply enterprise data quality methodologies and best practices
- Ensure solutions meet performance, scalability, and availability requirements
- Develop and enhance the organization's Data Quality Framework
- Document data quality rules and technical assets within the enterprise data governance platform
- Ensure compliance with internal architecture, governance, and development standards
- Promote data quality best practices across development teams
- Develop end-to-end reconciliation processes for enterprise data
- Integrate data from multiple internal and external sources
- Build consolidated data models for downstream processing
- Implement reconciliation rules defined by business analysts
- Produce consolidated datasets including issue categorization and audit information
- Maintain historical audit trails to monitor data evolution over time
- Design and optimize large-scale data processing jobs
- Develop high-performance ETL and data integration processes
- Monitor data pipelines and job dependencies
- Perform root cause analysis for processing failures
- Conduct impact assessments and implement enhancements as business requirements evolve
- Develop statistical and reporting datasets
- Build reusable data assets that support business reporting
- Perform complex SQL queries and data analysis
- Support enterprise data cleansing and data quality initiatives
- Support enterprise IT transformation and migration projects with a strong data quality component
- Collaborate with Agile delivery teams throughout the project lifecycle
- Participate in: Sprint Planning, Backlog Refinement, Peer Reviews, Retrospectives, Release Planning
- Communicate progress, risks, and deliverables to technical and business stakeholders
- Load and integrate external data files into enterprise data models
- Implement reconciliation logic
- Build consolidated audit datasets
- Maintain historical audit tracking
- Produce reporting and statistical tables
- Monitor processing workflows and dependencies
What they ask
- Master's degree in: Business Analytics, Industrial Engineering, Data Science, Computer Science, Information Technology, or equivalent professional experience
- Minimum 8 years of experience developing enterprise data solutions
- Strong background in data quality, data engineering, or enterprise data management
- Experience delivering large-scale data-driven IT solutions
- Telecommunications industry experience is considered an an advantage
- Mandatory technical skills: SQL, Python, Apache Spark, Bash scripting
- Preferred technical skills: Pandas, GitHub, GitLab CI/CD pipelines, Data Quality Frameworks, Enterprise Data Governance, Collibra, Data Reconciliation, ETL Development
- Strong analytical and problem-solving skills
- Excellent organizational and planning abilities
- Strong communication and stakeholder management skills
- Ability to explain technical concepts to business users
- Experience working within Agile delivery environments
- Strong collaboration and mentoring capabilities
- Results-oriented with attention to detail
- Ability to manage multiple priorities simultaneously
- Continuous improvement mindset
- Fluent in English and Dutch or Fluent in English and French
Practical
- Agile development environment
- Cross-functional collaboration with business and IT teams
- Enterprise-scale data quality initiatives
- Participation in CI/CD and modern DevOps practices
How to apply
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