Be able to analyze data sources and identify a path to data science integration based on use cases.
Determine the scope and type of data for Customer Data Platform and Marketing Automation Platform
Take responsibility for analyzing and optimizing the performance of ETL processes
Define merging and data policies based on business needs
Selection of required data models for ML-based use cases
You have in-depth knowledge of both relational and non-relational database management systems and cloud-based data storage solutions (e.g. Amazon S3, Google Cloud Storage, Redshift, DynamoDB, Snowflake, Databricks, etc.)
You are familiar with designing and creating data models in relational and non-relational environments based on business needs.
You are proficient in handling event streaming technologies (e.g. Kafka, Solace) and ETL tools (e.g. Informatica, Pentaho etc.)
You understand the business value of applying machine learning in the context of customer data and marketing use cases
Hands-on experience in Python (or similar programming language - e.g. Java) development and knowledge of versioning control systems would be an advantage
You have good presentation and communication skills in English (at least C1) and ideally also in German (B2)