About this role
Sector: Telecommunications Employment Type: Contract Location: Belgium (Hybrid) 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. ... ... 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