Friedbert W. - Data Analyst / Business Analyst

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Ihringen, Germany

Experience

Mar 2025 - Present

9 months

Data Analyst / Business Analyst

Profilmetall

Analysis and development of a new reporting system in Power BI (production data)

Building a data model in Power BI
Creating interactive dashboards and reports with Power BI, Power BI Embedded
Implementing security and access models at row-level and object-level
Data modeling: designing and implementing an automated and scalable report model in Power BI
DAX development: applying complex DAX queries
Reporting and dashboard development: designing interactive dashboards and reports that provide clear KPI visualizations to support decision-making
Collaboration and stakeholder management: working closely with in-house and client service management teams to implement data requirements accurately and communicate results effectively
Reviewing and improving data quality
Training employees

Oct 2024 - Mar 2025

6 months

Data Analyst / Business Analyst

Axa

Analysis and development of a new reporting system from two legacy systems in Snowflake

Building a data model in Snowflake
Creating reporting with Power BI (MVP)
Implementing row-level and object-level access control
Analyzing payment system based on ISO 20022
Data modeling: designing and implementing an automated and scalable report model in Power BI
DAX development: applying complex DAX queries and creating calculated columns
Reporting and dashboard development: designing interactive dashboards and reports that provide clear KPI visualizations to support decision-making
Collaboration and stakeholder management: working closely with in-house and client service management teams to implement data requirements accurately and communicate results effectively
Reviewing and improving data quality
Data modeling: designing and implementing an automated and scalable report model in Power BI
Testing created data models (data modeling)
Methods and tools: Power BI, Snowflake, Jira, Confluence, Git/GitHub

Jan 2024 - Sep 2024

9 months

Data Analyst / Business Analyst / Teilprojektleiter

VDI

Analysis and development of member reporting (CRM), analysis of various marketing projects

Creating interactive dashboards and reports with Power BI, Power BI Embedded
Data modeling: designing and implementing an automated and scalable report model in Power BI
DAX development: applying complex DAX queries and creating calculated columns
Reporting and dashboard development: designing interactive dashboards and reports that provide clear KPI visualizations to support decision-making
Collaboration and stakeholder management: working closely with in-house and client service management teams to implement data requirements accurately and communicate results effectively
Data analysis in marketing and CRM
Implementing row-level (RLS) and object-level (OLS) security
Creating a channel reporting system
Reviewing and improving data quality
Testing created data models (data modeling) in Dataverse
Troubleshooting old Power BI dashboards
Analyzing Google Analytics 4 data
A/B test analysis
Web dashboard in Looker
Methods and tools: Power BI, Microsoft Dynamics NAV, Business Central, Google Analytics (GA4), Google Tag Manager, Jira, Confluence

May 2023 - Dec 2023

8 months

Data Engineer / Data Scientist / Business Analyst / Teilprojektleiter

Fressnapf-Tiernahrungs GmbH

Subproject 1: analysis and reorganization of company-wide material master data. Subproject 2: data preparation and analysis of online marketing data

SAP R3, SAP S4 HANA
Replacing SAP SAC
Data analysis and transformation with R and Python
Creating reports with R
Supporting enterprise architecture
Building data structures for eCommerce
Creating a channel reporting system in Power BI
Developing and implementing data governance guidelines
Responsible for data quality
Creating a data model (data modeling)
Testing created data models
Implementing row-level (RLS) and object-level (OLS) security
Database queries with SQL and PL/SQL
Creating interactive dashboards and reports with Power BI, Power BI Embedded
Data modeling: designing and implementing an automated and scalable report model in Power BI
DAX development: applying complex DAX queries and creating calculated columns
Reporting and dashboard development: designing interactive dashboards and reports that provide clear KPI visualizations to support decision-making
Collaboration and stakeholder management: working closely with in-house and client service management teams to implement data requirements accurately and communicate results effectively
Creating statistical models and predictive analytics simulations with Python (NumPy, SciPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow)
Testing and documenting developed solutions
Process analysis of data flows, requirements engineering, process capture and visualization
Methods and tools: SAP R3/Hana, MS SQL Database, Oracle Database, Power BI, Microsoft SQL Server Integration Services, Google Analytics (GA4), Google Tag Manager, R, Python, Jira, Confluence, Git

Apr 2022 - Feb 2023

11 months

Data Engineer / Data Scientist

IDT Biologika

Developing GMP-compliant analysis software for monitoring process data in quality and production. Data sources were MS SQL databases and SAP system. Creating KPI reports with Power BI.

SAP ERP
MS SQL Database, MariaDB
Requirements engineering
Analyzing production data and visualizing data with R and R-Shiny
Creating reports with R Shiny
Process analysis of data flows, process capture and visualization
Creating a data model (data modeling) in Snowflake
Testing created data models
Replacing SAP SAC; creating dashboards with Power BI
Testing and documenting developed solutions
Methods and tools: SAP R3, R, Shiny, ShinyProxy, MS SQL Database, Microsoft SQL Server Integration Services (SSIS), Snowflake, Linux, Docker, Power BI, Git

Jun 2021 - Mar 2022

10 months

Data Engineer / Data Scientist / Business Analyst / Subproject Manager

Fielmann

Subproject 1: set up reporting for eCommerce activities (CRM and Marketing) Subproject 2: analysis and reorganization of the company-wide material master data for the "Digitalization and eCommerce" project

SAP R3 / SAP S4/HANA
Oracle databases, MariaDB
building ETL pipelines
migrating reports from Qlik Sense to Power BI
creating interactive dashboards and reports with Power BI, Power BI Embedded
analyzing and transforming data with R and Python
optimizing data structure for faster access
supporting enterprise architecture
building data structure for eCommerce
setting up channel reporting in Power BI
creating a data model in Snowflake
Power BI reporting of marketing data
developing and implementing data governance guidelines
responsible for data quality
testing created data models
database queries with SQL and PL/SQL
creating dashboards with Power BI
implementing row-level (RLS) and object-level (OLS) security
data modeling: designing and implementing an automated and scalable report model in Power BI
DAX development: applying complex DAX queries and creating calculated columns
reporting and dashboard development: designing interactive dashboards and reports that clearly visualize KPIs and support decision-making
collaboration and stakeholder management: working closely with in-house and client service management teams to implement data requirements accurately and communicate results effectively
testing and documenting developed solutions
process analysis of data flows, process documentation, and visualization
building statistical models and predictive analytics simulations with Python (NumPy, SciPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow)
methods and software tools: SAP R3 / HANA, Kafka Stream, MS SQL Database, Microsoft SQL Server Integration Services, R, Python, JSON filesystem, Oracle DB, Snowflake, Power BI, Qlik Sense, Jira, Confluence, Google Analytics, Google Tag Manager, Git/GitHub

Nov 2020 - Mar 2021

5 months

Power BI Software Developer, Data Scientist, Business Analyst

mySolution

Development of dashboards for the assfinet database

creating a data model
testing created data models
migrating from Qlik to Power BI
creating interactive dashboards and reports with Power BI, Power BI Embedded
testing and documenting developed solutions
creating DAX scripts
testing and documenting developed solutions
analyzing data
methods and tools: MS Power BI, Qlik, SQL database (assfinet)

Aug 2020 - Dec 2020

5 months

FORTRAN and Python Software Developer

RWE Energie

Analysis and modification/optimization of simulation program in water management

migrating software to the latest release
optimizing parallelization
optimizing OpenMP code
analyzing and optimizing virtual machines
building data model in Snowflake
software validation
running simulations
building statistical models and simulations with Python (NumPy, SciPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow)
methods and software tools: Microsoft Visual Studio, Intel Parallel Studio XE FORTRAN, MS Azure Cloud, Snowflake, Citrix, Jira, Confluence, Git/GitHub

Dec 2019 - Jul 2020

8 months

Rendsburg, Germany

Project Manager and R/Python Software Developer; Data Engineer, Data Scientist

Mechanical Engineering Company

Analysis of production data to reduce rework and errors

planning, execution, and building ETL pipelines
creating database in Azure Cloud
analyzing data
data visualization with Power BI
anomaly detection in data sets
building statistical models and simulations
developing ML models to reduce rework (supervised and unsupervised learning) with Python
building statistical models and simulations with Python (NumPy, SciPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow)
deploying machine learning models in Azure Cloud
validating simulation models
measurement analysis
methods and software tools: R, interactive Shiny app, MS Azure Cloud, Python, Talend (ETL), Power BI and Excel, Jira, Confluence, Git/GitHub

Jan 2019 - Present

6 years 11 months

Google Analytics Data Analyst

Various Tourism Boards

ongoing analysis with Google Analytics.

Jan 2019 - Jun 2019

6 months

Marburg, Germany

Project Manager and Software Developer R and Excel

Pharmaceutical Industry

Risk simulation using the Monte Carlo method in project management

Introducing the Monte Carlo method for project management
Training employees on the Monte Carlo method
Evaluating different software vendors
Simulating project plans for time and cost
Creating statistical models and simulations
Methods and software tools: Statistical simulations, Monte Carlo method, R, Excel, Vose Software, @RISK, Oracle Crystal Ball Suite, Power BI

Nov 2018 - Jan 2019

3 months

Project Manager and Software Developer R, Python and SQL / Data Analyst / Machine Learning

Aviation Supplier

Building an SPC system in MEMS production

Connecting production equipment
Setting up the ETL pipeline to SAP R3 / SAP BW
Creating SAP tables
Developing statistical models
Detecting anomalies in datasets
Introducing and training on the SPC method
Creating statistical models and simulations with Python
Creating statistical models and simulations with Python (Numpy, Scipy, Pandas, Matplotlib, Seaborn, Scikit-Learn, Tensorflow)
Building machine learning models (supervised and unsupervised learning) with Python
Deploying ML models in Azure Cloud
Data visualization with Power BI
Methods and software tools: SAP, R, R-Studio, SQL, MS Azure Cloud, ETL processes, Python, R Machine Learning and Power BI

May 2018 - Dec 2018

8 months

Project Manager and Software Developer R, Python and SQL / Data Analyst

Aviation Supplier

Correlation analysis for fiber sensors

Connecting production equipment
Setting up the ETL pipeline to SAP
Creating SAP tables
Preparing data for correlation analysis
Detecting anomalies in datasets
Linking data from different production steps
Predictive analytics modeling with Python
Creating statistical models and simulations with Python (Numpy, Scipy, Pandas, Matplotlib, Seaborn, Scikit-Learn, Tensorflow)
Building machine learning models (supervised and unsupervised learning)
Creating statistical models with Python
Data visualization with Tableau

The goal of the project was to link test data from production processes to analyze the impact of various factors occurring during production. From the analysis of large datasets (several gigabytes), we identified which factors have a decisive impact on the final product quality.

Methods and software tools: R, R-Studio, Predictive Analytics, Python, Machine Learning, visualization with Shiny or Tableau, deployment in MS Azure Cloud.

Jan 2018 - Dec 2018

1 year

Project Manager and Software Developer R and Python; Implementation of Google Analytics and GMT on various websites

Travel Service Provider

Text mining: Facebook and Twitter reactions

Analyzing user reactions to marketing campaigns
Analysis with NLP (Python and R)
Analyzing user behavior
Analyzing customer feedback
Analysis with Google Analytics
Applying and analyzing GIS data
Building statistical models for customer retention with Python
Creating reports from Google Analytics
Data visualization for each tourism board in Power BI or Tableau
Ongoing analysis with Google Analytics since 2019 for various tourism boards
Methods and software tools: R, R-Studio, visualization with Shiny, Predictive Analytics, CRM system, Power BI, Tableau, Machine Learning and Python

Jan 2018 - May 2018

5 months

Data Engineer / Data Scientist

Pharmaceutical Manufacturer

Validation of testing methods in the medical field

Validating physical, chemical and biological testing methods
Creating test plans
Writing reports
Analyzing experimental data with R and R-Shiny
Building statistical models with Python
Data visualization with Power BI

Validation of testing methods in the medical field; statistical analysis

Methods and software tools: Minitab, R, interactive Shiny app, Power BI

Sep 2017 - Apr 2018

8 months

Project Manager and Software Developer R, Python and SQL / Data Analyst

Aerospace Supplier

Predictive maintenance in production area

Built the ETL pipeline to SAP
Created SAP tables
Prepared data for predictive maintenance
Developed predictive maintenance models with Python
Built statistical models and simulations with Python (NumPy, SciPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow)
Deployed ML models in Azure Cloud
Created statistical models with Python
Data visualization with Power BI
Methods and software tools: analysis with R, Python, and RapidMiner. Working in MS Azure Cloud.

Jul 2017 - Jan 2020

2 years 7 months

Project Manager for Software Quality

Aerospace Supplier

Quality engineer for certification under DO-254 (hardware) and DO-178 (software) each at the highest criticality level DAL A

The certification projects were carried out under the DO-178 (software, DAL A) and DO-254 (hardware, DAL A) regulations.

As a quality engineer I was responsible for:

Creating process-compliant planning documents
Development processes (requirements engineering)
Planning and executing validation (including FPGA, VHDL code)
Planning and executing verification (including FPGA, VHDL)
Planning and executing system tests (flight tests, performance tests, hardware and software tests, EMC tests)
Participating in audits by the certification authority (EASA)
Methods and software tools: document reviews, Jira, Confluence, SVN and Git

Jun 2017 - Jun 2017

1 month

Lean Six Sigma Black Belt

Continental

Value stream analysis in production

Carried out value stream analysis as part of a task force to solve production problems (throughput, delivery deadlines)
Methods and software tools: value stream analysis

May 2017 - Oct 2017

6 months

Software Developer R, Python and SQL / Data Analyst

Automotive Manufacturer

Development of an analytical environment for big data; Technical Architect (Predictive) Analytics

Installation and management using Ambari (Hortonworks)
3-node cluster installation; Lambda architecture with Kafka as the ingestion layer, speed layer with Storm
Batch layer (Spark)
Data storage in various databases (HBase, Cassandra, MongoDB, HDFS)
Analysis was mainly done with Python and R
Built predictive analytics with Python
Created statistical models and simulations with Python (NumPy, SciPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow)
Built and maintained an ETL process with Talend
Tested Splunk
SQL and NoSQL databases
Application/analysis of GIS data
Methods and software tools: Hadoop ecosystem; AWS Cloud, machine learning, R and visualization with an interactive Shiny app

Jan 2017 - Jun 2017

6 months

Statistician and Software Developer R / Data Analyst / Six Sigma Black Belt

Medical Device Manufacturer

Data analysis in the development process in the medical field; carried out a DOE, details are confidential

Analysis of development and production data
Conducted DOE
DOE analysis
Created statistical models with Python and R
Data visualization with Power BI
Methods and software tools: analysis with R, Python, Minitab, visualization with Power BI

Jan 2017 - Jun 2017

6 months

Statistician / Data Analyst

Travel provider

Data analysis in the tourism sector. Building a CRM system in tourism, details are confidential.

The project goal was to derive a statement about customer satisfaction in the tourism sector from reactions to posts on Facebook and Twitter. Developed a customer retention model
Methods and software tools: Analysis with R, Python, RapidMiner, Power BI, big data technologies, CRM, predictive analytics with Google Analytics

Aug 2016 - Dec 2016

5 months

Statistician

Heavy industry company

Setting up quality management for production data; coaching employees

The project goal was to link test data from production processes to analyze the impact of various factors arising during production. The analysis of large datasets (several gigabytes) showed which factors have a decisive effect on the final product quality.
Methods and software tools: Data from SAP R3, CSV files, Excel files; visualization with Tableau or Power BI; statistical analysis; predictive maintenance

Aug 2016 - Dec 2016

5 months

Statistician / Data Analyst

Thyssenkrupp Rasselstein GmbH

Process optimization of a 600 m rolling mill with DOE

Analysis of production data
Conducting DOE
Analysis of DOE
Creating statistical models
Methods and software tools: Analysis with Minitab and R, visualization of results with Power BI

Jun 2015 - Dec 2015

7 months

Project manager and software developer (R, Python and SQL) / Data Analyst

Aerospace supplier

Introduction of SPC via SAP

This project was a continuation of the ‘Introduction of SPC connected workstations (INDUSTRY 4.0)’ project. The main extension was integrating SAP R3.
Methods and software tools: Querying production data from SAP and CSV files; analysis using Excel, R, Python, RapidMiner, Minitab; building predictive analytics models

Jan 2015 - Jun 2015

6 months

Project manager and software developer (R, Python and SQL) / Data Analyst

Aviation company

Building an MES system based on SAP R3, introducing production tracking (custom production, small batches), coaching team leaders and department heads in production

The goal of the project was to build an SPC system (statistical process control). This system captured process parameters and evaluated them statistically to ensure process stability in manufacturing. The main goal was to detect process changes early, e.g. wear.
The graphical presentation of results was mainly done with Tableau.
Methods and software tools: Visualization with Tableau, Qlik; coaching project managers; predictive analytics for delivery reliability

Jan 2015 - Jun 2015

6 months

Project Manager and Software Developer R, Python, and SQL / Data Analyst

Aerospace Supplier

Introduction of SPC connected workstations (INDUSTRY 4.0), employee coaching

The goal of the project was to build an SPC system (statistical process control). With this system, process parameters were collected and evaluated statistically to guarantee the stability of the manufacturing process. The main objective was to detect process changes, e.g., wear, at an early stage.
The graphical visualization of the results was mainly done with Tableau.
The results were used by team leaders and department heads in production.
Methods and software tools: analysis with Excel, R, Python, RapidMiner, Minitab, Tableau

Jan 2014 - Present

11 years 11 months

Freelance Senior Consultant

Jan 2010 - Dec 2023

14 years

Quality Process Engineer Black Belt Lean Six Sigma ISO 9001/9100

Northrop Grumman LITEF GmbH

Jan 2007 - Dec 2010

4 years

Lean Six Sigma Black Belt

Northrop Grumman LITEF GmbH

Jan 2000 - Dec 2007

8 years

Group Leader Production Engineering

Northrop Grumman LITEF GmbH

Jan 1999 - Dec 2000

2 years

Development Engineer

Northrop Grumman LITEF GmbH

Jan 1988 - Dec 1999

12 years

Wuppertal, Germany

Senior Engineer

University of Wuppertal

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

BB Reduction of test repeats in TFT
Background: μFORS test repeats (rework and deviations) are a significant part of the μFORS failure statistics and deviations in the manufacturing results. Currently, it cannot be determined whether the failures should be attributed to the device under test or the tester.
Goals:
Reduce μFORS test repeats by 50%,
thus reduce deviation time by 30%,
thereby increase TFT test capacity by 20%

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

BB Scoping LCR-100
Background: Identify factors influencing LCR-100 performance, improve Rockwell Collins customer satisfaction (guideline for discussions with RCI Black Belts), and reduce the effort of providing data to assess LCR-100 performance.
Goals:
Visualize and evaluate disturbance factors in the LCR-100 processes, including their impact on performance and their coverage by ongoing activities or projects.
Analyze performance data from three batches of 10 systems each and present it in a Six Sigma format for discussions with Rockwell Collins Black Belts (customer satisfaction).
Perform a combined evaluation of Cal/ATP, FOGIMU-CAS, and bias test.
Test a presentation format for these datasets.
Automate the provision of LCR-100 performance data.
Reduce the effort required to prepare data from SAP into a tested display.
Establish a company-wide unified data base as an analysis and evaluation tool.

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

BB Reduction of B290 cycle time
Background: The cycle time in the production of the B-290 sensor is too high and needs to be reduced. Until now, there have been no measurements of the cycle time, so the baseline can only be determined in the Improve phase. However, since production is a bottleneck, a significant reduction is required.
Goal:
Reduce cycle time by 20% (based on measurements).

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

BB cost reduction in inspection effort
Background: The costs for intermediate inspections and internal QA approvals amount to about €700,000 per year. These costs should be analyzed as part of the project and savings potential identified.
Goal:
Intermediate inspections and internal QA approvals cost about €700,000 per year. These costs should be reduced by about 14%, so that savings of about €100,000 per year can be achieved.

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

BB risk minimization for TO-TxRx module
Background: To stay competitive, the production costs for the uFORS-6U need to be reduced by 30% through a redesign. To achieve this goal, the risks associated with introducing new technologies or components must be minimized in advance through analysis and testing. It must be ensured that the savings are not offset by lower yield and high rework.
Goals:
Minimize risks, functional prototypes on the first try;
Estimate expected yield.

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

GB effort reduction in presenting test results in the TFT area
Background: In the TFT area, test results are always printed in full. These detailed result printouts are not used everywhere or only sampled for evaluation. In a "normal" test run on the LCR-100, 120 pages of test results are produced, which already exist electronically as raw data. In this project, we want to reduce this effort, printing, and filing. Additionally, the device folders and thus the test results are completely scanned after device delivery. Here, too, an effort reduction should be achieved.
Goals:
Reduce paper usage by 225,000 sheets
Reduce scanning time by about 625 hours per year.

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

GB effort reduction in approval process
Background: During the development and product maintenance process, all changes must be filed through the official change management in SAP. About 1,400 documents are processed in the change management system each year.
Goal:
The goal of the project is to optimize the approval process so that a significant reduction in time is achieved, from about 60 minutes to 15 minutes.

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

GB effort reduction for EASA Form 1
Background: The EASA Form 1 is an airworthiness certificate issued for every civilian aircraft. The creation of the EASA Form 1 is currently done using MS Access. This poses a very high risk because MS Access databases are not maintained at NG LITEF.
Goal:
The goal of the project is to optimize the creation process to reduce time and significantly increase data security.

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

GB Automatic KAL evaluation μFORS
Background: The manual evaluation of the calibration results should be replaced by an objective, quantitative, automated assessment. The method should be easy to transfer to other μFORS derivatives.
Goals:
Eliminate manual KAL evaluation;
Principle: KAL PASS is a clear PASS

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

GB Effort reduction in change service
Background: Reduce administrative effort while shortening the lead time of change orders. Implement transparency of the status of each change order in SAP.
Goal:
Reduce effort for approving change orders by 1260 hours. Equivalent to: 108,000 per year

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

GB Reduction of PC boot times
Background: PC boot times continuously increase with the PCs' age. This trend hinders employees in their daily work.
Goal:
Reduce the continuously increasing PC boot times by at least 1 minute on average and ensure sustainability of the reduced time

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

GB High availability test computers
Background: Significantly reduce test equipment failures due to network, server, and computer influences and ensure high availability in the future.
Goal:
Reduce test equipment failures from 32 per year to 5 per year.

Lean Six Sigma Project

Northrop Grumman LITEF GmbH

GB Reduction of LOOP in the AHRS O&R area
Background: Almost 15% of repairs require more than two loops before they can be delivered again. The repeated loops have complex causes such as test equipment errors, insufficient inspections, etc. This project aims to find out, among other things, if there are dependencies related to the product, the application, the user, etc., and what early detection options exist to prevent loops from happening in the first place.
Goal:
The goal is to reduce or avoid additional loops through better device inspection. Based on PLK 12.02.

Summary

Acquiring, processing and analyzing large data sets is part of my daily work. The data sets to be analyzed were sourced from various sources and loaded into databases with ETL processes and further processed with predictive analytics. My software focus is on Python and R. For visualization I mainly work with Tableau, Qlik and Power BI.
Summary of my experience from various BI projects:
Creation of interactive dashboards and reports with Power BI, Power Platform, Power BI Embedded
Development of KPIs and trend analyses
Customizing visualizations to the client's corporate design
Querying various data sources and databases in different data formats
Database queries with SQL and PL/SQL
Integration of GIS data into reports
Knowledge of SAP/R3 and SAP S/4HANA
Very good skills in SAP SAC
Extensive experience with Azure and AWS cloud platforms
Extensive experience with the cloud-based data platform Snowflake
Linking Power BI with Microsoft Dynamics and SAP applications
Creating data models in Snowflake
Broad experience in Power Query, DAX, DAX Studio, Direct Query
Very good skills in SQL queries (MS-SQL, MariaDB, Snowflake SQL)
Very good skills in Python and R/Shiny
Strong knowledge in statistics and machine learning
Creating ETL workflows with Python, Talend, PowerShell and R
Gathering business requirements (Requirement Engineering)
Very good knowledge of Microsoft SharePoint, Microsoft 365 (e.g., Excel)
MS BI technologies (MS SQL Server, SSIS, SSRS, Power BI, Visual Studio with Data Tools, Dataverse)
Very good skills in data quality and data cleaning
Experience in conducting proof of concepts
Version control with Git/GitHub
Extensive experience with Power BI security and access concepts (row-level security and object-level security)
Training employees in Power BI

Languages

German

Native

English

Intermediate

Education

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Dr.-Ing. · Telecommunications

Certifications & licenses

Lean Six Sigma ISO 9001/9100

LITEF GmbH

Lean Six Sigma Black Belt

LITEF GmbH

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