Innova - Senior Data Quality Developer

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.
• 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