Senior Data Quality Developer
Sector: Telecommunications
Employment Type: Contract
Location: Belgium (Hybrid)
Mission Overview
As a Senior 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.
Key Responsibilities
Data Quality Development
- 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.
Data Quality Framework & Governance
- 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.
Data Integration & Reconciliation
- 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.
Data Engineering
- 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.
Reporting & Analytics Support
- 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.
IT Project Support
- 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.
Key Functional Areas
Joint Venture End-to-End Audit
- 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.
Customer Device Audit
- Integrate data from multiple enterprise source systems.
- Develop data quality and reconciliation processes.
- Support data cleansing initiatives.
- Deliver actionable insights through optimized SQL queries.
IoT Services Audit
- Audit IoT services using metadata-driven methodologies.
- Develop efficient processing jobs for large-scale datasets.
- Improve processing performance and scalability.
Geospatial Data Quality
Perform consistency and quality validation between enterprise master data and data warehouse information, including:
- Geographic addresses
- Buildings
- Building units
- Geospatial reference information
Required Qualifications
- Master's degree in:
- Business Analytics
- Industrial Engineering
- Data Science
- Computer Science
- Information Technology
- Or equivalent professional experience
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 advantage.
Technical Skills
Mandatory
- SQL
- Python
- Apache Spark
- Bash scripting
Preferred
- Pandas
- GitHub
- GitLab
- CI/CD pipelines
- Data Quality Frameworks
- Enterprise Data Governance
- Collibra
- Data Reconciliation
- ETL Development
Core Competencies
- 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
Languages
- Fluent in English and Dutch or
- Fluent in English and French
Work Environment
- Agile development environment
- Cross-functional collaboration with business and IT teams
- Enterprise-scale data quality initiatives
- Participation in CI/CD and modern DevOps practices
