About this role
Responsibilities Develop and maintain data quality checks using Python and Spark within the established technical framework. Translate business requirements into technical solutions by evaluating feasibility and workload for data quality developments. Lead the development team in applying best practices and standard methodologies for high-performance data delivery. Manage end-to-end data reconciliation processes, including data ingestion and integration into consolidated models for infrastructure partnerships. Create and maintain audit trails and statistical tables to support business reporting and historical data tracking. Conduct impact analysis and perform root cause analysis on data processing chains to ensure system reliability. Requirements 8+ years of experience in developing and rolling out IT solutions with a strong data component. You bring advanced expertise in data processing with Python , Spark , and Bash . You possess strong proficiency in SQL for querying complex structured datasets and extracting insights. You have experience managing end-to-end data reconciliation, data modeling, and ingestion of various file formats. You bring a background in Agile environments and CI/CD release cycles across multiple environments. You're a holder of a Master’s degree in Business Analytics, Industrial Engineering, Data Science, or equivalent experience. You possess advanced analytical, problem-solving, negotiation, and organizational skills. You are fluent in English with active knowledge of Dutch or French . Nice to Haves Experience with Pandas and other common Python data libraries. Practical knowledge of CI/CD pipelines and version control using GitHub or GitLab . Professional experience within the telecommunications sector. Knowledge of data governance tools such as Collibra .