Role description

• Datasets and data pipelines preparation, support for Business, data troubleshooting.

• Closely collaborate with the Data & Analytics Program Management and stakeholders to co-design Enterprise Data Strategy and Common Data Model

• Implementation and promotion of Data Platform, transformative data processes, and services

• Develop data pipelines and structures for Data Scientists, testing such to ensure that they are fit for use

• Maintain and model JSON based schemas and metadata to re-use it across the organization (with central tools)

• Resolving and troubleshooting data related issues and queries

• Covering all processes from enterprise reporting to data science (incl. ML Ops)

Experience

• Hands-on Big Data experience using common open-source components (Hadoop, Hive, Spark, Presto, NiFi, MinIO, KBS, Kafka)

• Experience in stakeholder management in heterogeneous business/technology organizations

• Experience in banking or financial business, with handling sensitive data across regions

• Experience in large data migration projects with on-prem Data Lakes

• Hands-on experience in integrating Data Science Workbench platforms (e.g., Knime, Cloudera, Dataiku))

• Track record in Agile project management and methods (e.g., Scrum, SAFe).

Skills

• Knowledge of reference architectures, especially concerning integrated, data-driven landscapes and solutions

• Expert SQL skills, preferably in mixed environments (i.e. classic DWH and distributed)

• Working automation and troubleshooting experience in Python using Jupyter Notebooks or common IDEs

• Data preparation for reporting/analytics and visualization tools (e.g. Tableau, Power BI or Python based)

• Applying a data quality framework within the architecture

• Good knowledge of German is beneficial, excellent command of English is essential