01/27/2026 updated


100 % available
Senior AI Engineer & Data Science Consultant, Developer, Architect, and Project Lead
München, Germany
Worldwide
M.Sc. Applied Stochastics, M.Sc. Cognitive Science, B.Sc. Mathematik/Informatik, B.Sc. Cognitive Science10+ years experience in Data Science and Data Engineering.
5+ years experience in Data Consultancy.
Selected Programming Languages:
Julia, Python, R, SQL, Scala, Matlab, Java, C++, Haskell, ROS, JavaScript, HTML, CSS (Web Stack)
Selected Industries:
Telecommunication, Automotive, Retail, Bonus Program, Media, Manufacturer
Selected Data Science Fields:
Statistics, Machine Learning, Deep Learning, Computer Vision, NLP Natural Language Processing, Analytics, Anomaly Detection, Time Series Prediction, Recommendation, Object recognition, ETL, Data Pipelines, Data Lake, Visualization, Dashboards
Selected Big Data:
Julia, Dask, PySpark, Spark, Hadoop MapReduce, Data Lake Setup, Yarn, HDFS, Hive, HBase
Selected Database:
PostgreSQL, MongoDB, MySQL, Oracle, Microsoft, Hive, HBase
Cloud:
AWS, Azure, Infrastructure-as, code, terraform, cloudformation, sceptre
AWS:
S3, SNS, Kubernetes, AWS VPC, ETL, CRM, API, pandas, AWS SNS, AWS SQS, PostgreSQL, MongoDB, AWS DocumentDB, AWS API Gateway, AWS Cognito, AWS Lambda, infrastructure-as-code cloudformation, Lambda, AWS Transit Gateway, AWS Networking, EC2, AWS Session Manager, AWS CloudWatch
Azure:
Azure Machine Learning, Azure App Service, Azure AD, infrastructure-as-code terraform
Methodology:
Scrum, Waterfall
5+ years experience in Data Consultancy.
Selected Programming Languages:
Julia, Python, R, SQL, Scala, Matlab, Java, C++, Haskell, ROS, JavaScript, HTML, CSS (Web Stack)
Selected Industries:
Telecommunication, Automotive, Retail, Bonus Program, Media, Manufacturer
Selected Data Science Fields:
Statistics, Machine Learning, Deep Learning, Computer Vision, NLP Natural Language Processing, Analytics, Anomaly Detection, Time Series Prediction, Recommendation, Object recognition, ETL, Data Pipelines, Data Lake, Visualization, Dashboards
Selected Big Data:
Julia, Dask, PySpark, Spark, Hadoop MapReduce, Data Lake Setup, Yarn, HDFS, Hive, HBase
Selected Database:
PostgreSQL, MongoDB, MySQL, Oracle, Microsoft, Hive, HBase
Cloud:
AWS, Azure, Infrastructure-as, code, terraform, cloudformation, sceptre
AWS:
S3, SNS, Kubernetes, AWS VPC, ETL, CRM, API, pandas, AWS SNS, AWS SQS, PostgreSQL, MongoDB, AWS DocumentDB, AWS API Gateway, AWS Cognito, AWS Lambda, infrastructure-as-code cloudformation, Lambda, AWS Transit Gateway, AWS Networking, EC2, AWS Session Manager, AWS CloudWatch
Azure:
Azure Machine Learning, Azure App Service, Azure AD, infrastructure-as-code terraform
Methodology:
Scrum, Waterfall
Languages
DeutschNative speakerEnglischGoodNiederländischBasic knowledgeSpanischBasic knowledge
Project history
Supporting Usecase Development on Datalake
Guidance was provided for architectural decisions, adapting access policies, and debugging routing issues. A specific GDPR treatment ingestion processes was implemented and rolled-out. In production.
Duration: 6 months
Team setting: Team Lead, Team of 2, remote
Technologies: Infrastructure-as-code, cloudformation, sceptre, python, boto3, PySpark, scala, Spark, AWS Glue, AWS Secrets,
Guidance was provided for architectural decisions, adapting access policies, and debugging routing issues. A specific GDPR treatment ingestion processes was implemented and rolled-out. In production.
Duration: 6 months
Team setting: Team Lead, Team of 2, remote
Technologies: Infrastructure-as-code, cloudformation, sceptre, python, boto3, PySpark, scala, Spark, AWS Glue, AWS Secrets,
Everything around data science consultancy:
- recruiting new colleagues
- pitching new projects
- request for proposals
- requirements engineering
- team setup
- team lead
- conceptualization of data science or data engineering solution
- development of data science or data engineering solutions
- giving workshops, trainings
- auditing customers solutions
- architecting data lakes and cloud data infrastructure
- ...
- recruiting new colleagues
- pitching new projects
- request for proposals
- requirements engineering
- team setup
- team lead
- conceptualization of data science or data engineering solution
- development of data science or data engineering solutions
- giving workshops, trainings
- auditing customers solutions
- architecting data lakes and cloud data infrastructure
- ...
20 ETL Pipelines on AWS
Replacing an CRM required the development of about 20 ETL pipelines to replace existing systems with new data-flows. Including one REST API. In production.
Team setting: Team Lead, Team of 3, remote
Technologies: AWS Glue, PySpark, python, boto3, pandas, AWS SNS, AWS SQS, PostgreSQL, MongoDB, AWS DocumentDB, AWS API Gateway, AWS Cog
Replacing an CRM required the development of about 20 ETL pipelines to replace existing systems with new data-flows. Including one REST API. In production.
Team setting: Team Lead, Team of 3, remote
Technologies: AWS Glue, PySpark, python, boto3, pandas, AWS SNS, AWS SQS, PostgreSQL, MongoDB, AWS DocumentDB, AWS API Gateway, AWS Cog