Markus L.

Data Engineer @ Degussa Bank

About

» Long time experience as Integration Developer and Data Engineer using IBM InfoSphere Datastage and the Microsoft Azure platform. » Actively supported many projects as a certified Scrum Master » Multiple experiences as a Deputy Team Leader. » Development and Integration of Continuous Integration (CI) and Continuous Delivery (CD) Pipelines. » Development of Python Backend Applications using Flask and FastAPI. » Development of Python Frontend Applications using HTML, CSS and JavaScript. » Optimization and Evaluation of LLM-Chatbot Applications.

Country

Germany

City

Frankfurt Rhine-Main Metropolitan Area

Industry

Banking

Skill

Data Engineering, Datenmanagement, Datenanalyse, Datenvisualisierung, Data Science, Big Data, Microsoft Azure, Azure Data Factory, Künstliche Intelligenz (KI), Azure Databricks, Agile Methoden, Extract, Transform, Load (ETL), DataStage, SQL, Python (Programmiersprache), Softwareentwicklung, Java, C (Programmiersprache), C++, R

Experience

Data Engineer

Degussa Bank

2022-7 - Present · 4 yrs 3 mos

Frankfurt/Rhein-Main

Data Engineer – Member of the Data Engineering Team

Integration Developer

Degussa Bank

2016-9 - 2022-6 · 5 yrs 10 mos

Frankfurt am Main, Hessen, Deutschland

Integration Developer – Member of the BI / Data Management Team

Studentische Hilfskraft

Degussa Bank

2011 - 2016-8 · 5 yrs

Frankfurt am Main, Hessen, Deutschland

Education

Fachhochschule Darmstadt

Informatik

2013 - 2016 · 3 yrs

» Topic of the Master’s Thesis: „A Pipeline of Differential Gene Expression Analysis“ » Brief Synopsis of the Research: The outcome of this thesis is a solution for scientists, which enables the possibility to apply differential expression analysis on RNAseq count data without having programming knowledge. Therefore several open source R analysis packages together with further functional components has been integrated into a pipeline, whereby the focus was to cover all necessary work steps and dependent tasks of a differential expression analysis. The users of the pipeline would benefit from the easy usage, fast and straight forward analysis setup and the fact that, if any, only one manual has to be read for the most use cases. » Final mark: 2.3

Frankfurt University of Applied Sciences

Informatik

2009 - 2013 · 4 yrs

» Topic of Studium Generale: “Erfolgreich Arbeiten im Ausland – Asiability” (trans.: “Successful working abroad – Asiability”) » Topic of the Bachelor’s Thesis: “Social Networking App für Android” » Final mark: 2.2