freiberufler Senior Data Engineer und Cloud Entwickler auf

Senior Data Engineer und Cloud Entwickler

zuletzt online vor wenigen Stunden
  • 120‐150€/Stunde
  • 77694 Kehl (Rhein)
  • Weltweit
  • de  |  fr  |  en
  • 26.07.2022


Eine engagierter Cloud Data Engineer und DevOps, der Unternehmen beim Aufbau ihrer DWH und Datenanalytics-Anwendungen unterstützt. AWS, Azure, Databricks, Spark, Kubernetes, Machine-Learning, Machine Learning Ops, Graph-Datenbank.

Ich biete

  • Amazon Web Services (AWS)
  • Apache Spark
  • Databricks
  • Datenanalyse
  • Java (allg.)
  • Kubernetes
  • Machinelles Lernen (allg.)
  • Microsoft Azure
  • Neo4j
  • Python

Projekt‐ & Berufserfahrung

Data and Cloud Engineer
Kundenname anonymisiert, Stuttgart
9/2021 – 7/2022 (11 Monate)

9/2021 – 7/2022


In order to migrate a classical machine learning model to Azure, which aims to predict the vehicle repair rate, I interpreted the Python project into Spark and used Databricks, MLflow and Azure Data Factory to automate the data ingestion and to parallelize the model training. Front-end data visualization uses Grafana. Tools: Azure Data Factory, Databricks, Spark, Delta Lake, Azure Pipelines, Grafana.

Eingesetzte Qualifikationen

Azure Databricks, Big Data, Continuous Delivery (CDE), Datenbankentwicklung, Kontinuierliche Integration (CI), Microsoft Azure, Python, Scala

Data Scientist and Cloud Engineer (Festanstellung)
Kundenname anonymisiert, Berlin
2/2020 – 8/2021 (1 Jahr, 7 Monate)
IT & Entwicklung

2/2020 – 8/2021


Kitchen furniture blueprints sometimes contain errors which should be avoided before being sent to construction. As a
technical team working with a kitchen provider, we received thousands of kitchen plans on a daily basis. I designed a graph model to
represent the furniture of a kitchen, geometric and graph algorithms to learn and look for errors in them, and a pipelined workflow on
Azure to process the data. Kitchen blueprints as data are first fed into the workflow by Kafka in real time, these are then validated
and sent to a Neo4j cluster by an Azure function. After the kitchen blueprints get ingested and analyzed by Neo4j, the result is sent
to the Cosmos DB and returned to the client, in case an error is detected or a warning occurred. Tools: knowledge graph, Kafka,
Neo4j, Azure Functions, AKS, Python and .NET.

Eingesetzte Qualifikationen

C#, Data Science, Kafka, Kubernetes, Microsoft Azure, Python

Data Scientist and Engineer
Kundenname anonymisiert, Peking
10/2018 – 1/2020 (1 Jahr, 4 Monate)
IT & Entwicklung

10/2018 – 1/2020


Astronomical data can be immense and requires a big data solution to process it. Working together with astronomers, I designed a Spark application for an on premise DWH to process the data and read in from and write out to its different layers. The application includes both batch processing to deal with existent data and streaming to deal with new data coming in. I also optimized the Spark application at different levels which has improved its performance remarkably. Tools: Spark 2.x, Kafka, Hadoop, Java.

Eingesetzte Qualifikationen

Apache Hadoop, Apache Spark, Java (allg.), Kafka, Machinelles Lernen (allg.)

Machine Learning Specialist
Kundenname anonymisiert, Huningue
4/2018 – 9/2018 (6 Monate)
Life Sciences

4/2018 – 9/2018


The combination of omic data and machine learning / deep learning is one of the cutting-edge areas of biopharma research. In this project where the company aims to get a better understanding of the high-throughput RNA sequencing data of patients undergoing different medical treatments after a myocardial infarction, my machine learning and deep learning algorithms came to help. Tools: Python and R.

Eingesetzte Qualifikationen

Machinelles Lernen (allg.), Python, Statistik (allg.)

Psychometry and AI
Kundenname anonymisiert, Rouffach
7/2017 – 8/2017 (2 Monate)

7/2017 – 8/2017


In the psychomotor therapy the diagnosis of schizophrenia had been to that date carried out by the observation and the subjective judgment of medical professionals. With the hope to develop an AI assistant helping physicians make better and more accurate clinical decisions based on more quantitative indicators, I built an application using machine learning and statistical models to predict schizophrenia. Tools: R.

Eingesetzte Qualifikationen

Machinelles Lernen (allg.), Statistik (allg.)

Kundenname anonymisiert, Shanghai
2/2016 – 8/2016 (7 Monate)
IT & Entwicklung

2/2016 – 8/2016


As a backend developer I participated in the development of a diagnosis assistant system, the goal of which is to detect among others pulmonary sarcoidosis using AI. Tools: .NET.

Eingesetzte Qualifikationen

.Net, Machinelles Lernen (allg.)

Financial Data Analyst
Kundenname anonymisiert, Luxemburg
11/2015 – 2/2016 (4 Monate)

11/2015 – 2/2016


As a risk analyst I ensured the role of developing statistical tools to monitor credit risk, market risk, liquidity risk and operational risk of the bank. Tools: R and Excel.

Eingesetzte Qualifikationen

Finanzanalyse, Risikomanagement (Finan.)


Data Science
Jahr: 2018
Ort: Lyon, Frankreich
(Master 1)
Jahr: 2017
Ort: Straßburg, Frankreich


C#, Java, Python, SAS, R, SQL, Neo4j, Docker, Machine-Learning, Datenanalyse, Biostatistik

Über mich

Mehrsprachiger, kommunikationsfreudiger Data Scientist bringt Ihnen Geschäftseinsichten aus Ihren komplexen Daten.

Persönliche Daten

  • Deutsch (Fließend)
  • Französisch (Fließend)
  • Englisch (Fließend)
  • Chinesisch (Muttersprache)
  • Europäische Union
  • Schweiz
6 Jahre und 9 Monate (seit 11/2015)
1 Jahr


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