You will be responsible for the development, maintenance, and optimization of data processing solutions within the Client Contribution platform.Key responsibilitiesDesigning and developing ETL/data transformation processes, implementing and maintaining Spark-based pipelines, supporting data integration initiatives, analyzing and troubleshooting data-related issues, and ensuring data quality and performance across the platform.The role requires hands‑on experience with Spark, SQL, (with Scala Python or Java), Databricks or similar Big Data environments, and Dev Ops practices.The candidate should be comfortable working in Agile teams, collaborating with functional and technical stakeholders, analyzing requirements, and contributing proactively to the continuous improvement of data solutions.Mandatory skills3+ years of experience in data and programmingGood SPARK basis + programming language that could be: Scala, Python or JavaAzure Databricks / Amazon EMR / Hive / Cloudera (or any Spark environment)Experience in reporting with Qlik SenseExperience working in agile continuous integration/Dev Ops paradigm and tool set (Git, Git Hub, Sonar, Nexus)Ability to work in a teamAbility to analyse requirements and cooperate with team members to improve itEnglish (at least B2+)Nice to have skillsInterest in leveraging AI‑assisted development tools and exploring AI‑driven approaches to improve data engineering, automation, and analytics processes will be considered a plus.
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