09.03.2025 aktualisiert


100 % verfügbar
Data Engineer, Data Analyst, Technology Lead
Putzbrunn, Deutschland
Weltweit
Bachelors of Engineering (Information Technology)Skills
Data AnalysisComputerprogrammierungDatenbankenDaasInformation EngineeringETLDatenvisualisierungGreenplumApache HadoopPythonMicrosoft Sql-ServerOracle FinancialsLumiraSAP ApplicationsSap HanaPL/SQLTableauTeradata SqlQliksenseSAP Business Objects
Database Developer: Hadoop, Aster Teradata, SAP HANA, MS-ACCESS , ORACLE, Teradata, MS-SQL, Greenplum
ETL Tools: Informatica, Business Objects Data Services
Visualization Tools: Tableau, QlikSense, SAP Lumira, SAP Business Objects
Programming: PL/SQL, Python
ETL Tools: Informatica, Business Objects Data Services
Visualization Tools: Tableau, QlikSense, SAP Lumira, SAP Business Objects
Programming: PL/SQL, Python
Sprachen
DeutschgutEnglischMuttersprache
Projekthistorie
? Project Profile-1:
Project Name Volkswagen Data Lab
Role Data Scientist and Technology Expert
Organization Volkswagen AG/AutoVision GmbH
Duration 91 months
Team size 80
Environment Cloud Environment: MS Azure (Databricks, Data Factory)
(with skill versions) Database: Oracle 11i, Aster Teradata, Hadoop, SAP HANA,
Greenplum, MS SQL
Tools: Informatica(ETL), Tableau(Reporting),
QlikSense(Reporting), SAP Lumira(Reporting),
BeyondCore(Analysis), Oracle APEX (Database Portal),
Splunk (Streaming Analytics)
Programming: Pl/SQL(Database), R Language
(Analysis), ORE (Database & Analysis), Python, Spark
O/s: Windows 10, Linux
? Project Description:
The Volkswagen Data Lab wants to develop and test IT solutions for the digital future of the
VOLKSWAGEN GROUP with the target of IT innovation leadership, Development and piloting of
new technologies, Cooperation with the most innovative technology companies worldwide,
Reduction of dependence on external service providers & agencies and Building strategic
partnerships.
Contribution:
1. Patents: Submission of 9 Invention disclosures and 3 are in the process of Patent filing.
2. After Sales: Development of intelligent algorithms for repeat repairs in after sales, dealer
fraud detection and dealer comparisons.
3. After Sales: Clustering on early defect warning system.
4. After Sales: Comparative analysis between different companies in After-Sales business.
5. After Sales: Clustering the customers and dealers in After-Sales business.
6. Connected Car: Analysis of connected car data especially weather relevant vehicle data
like temperature, sun intensity, rain and brightness to build a map layer with real-time
aggregated values which satisfies GDPR Anonymization, and provide these values to
Energy Providing Companies, which helps in better planning their energy production.
7. Connected Car: Analysis of Telematics data to prepare connected car project for
identification of relevant dealers' location based on customer driving behavior
8. Power Plants: Electricity Demand prediction for Power Plants
9. Sales: Predicting car sales and their configurations using machine learning techniques
10. Finance: Finance Margin Optimization of Trucks using machine learning techniques
11. Marketing: Analysis of customer visits to the workshop before and after recall campaign
12. Security: Developed an application for Car Theft Protection
13. Production: Digitalisation of the Production Platforms especially in Optimizing OEE
(Overall Equipment Efficiency)
14. Adhoc: Sales, Configurations and Social Media Analysis on Abgas Topic
15. Technical: Built an On-Premise based Data Lake Architecture which is implemented for 2
projects
16. Technical: Built a Cloud based Data Lake Architecture, which is implemented as
Digitalisation Platform for Cross-Functional applications. This project was implemented
with the help of Agile methods
17. Technical: Visualization of the end results of the project
18. Technical: Technology Scouting
19. Technical: Infrastructure Management
20. Technical: Data Management Support
21. Technical: Data Extraction, Transformation and Load
22. Technical: Learning New Data Technologies
23. Technical: Conducting workshops for the team members on new technologies
24. Technical: Taking Care of Technology Licenses
25. Technical: Data Security Management
26. Technical: Testing new technologies whether it is suitable for Data Lab or not and
documenting the same in internal Tech-Library
27. Technical: Data Lab Application Management
28. Technical: Installation of new technologies
Project Name Volkswagen Data Lab
Role Data Scientist and Technology Expert
Organization Volkswagen AG/AutoVision GmbH
Duration 91 months
Team size 80
Environment Cloud Environment: MS Azure (Databricks, Data Factory)
(with skill versions) Database: Oracle 11i, Aster Teradata, Hadoop, SAP HANA,
Greenplum, MS SQL
Tools: Informatica(ETL), Tableau(Reporting),
QlikSense(Reporting), SAP Lumira(Reporting),
BeyondCore(Analysis), Oracle APEX (Database Portal),
Splunk (Streaming Analytics)
Programming: Pl/SQL(Database), R Language
(Analysis), ORE (Database & Analysis), Python, Spark
O/s: Windows 10, Linux
? Project Description:
The Volkswagen Data Lab wants to develop and test IT solutions for the digital future of the
VOLKSWAGEN GROUP with the target of IT innovation leadership, Development and piloting of
new technologies, Cooperation with the most innovative technology companies worldwide,
Reduction of dependence on external service providers & agencies and Building strategic
partnerships.
Contribution:
1. Patents: Submission of 9 Invention disclosures and 3 are in the process of Patent filing.
2. After Sales: Development of intelligent algorithms for repeat repairs in after sales, dealer
fraud detection and dealer comparisons.
3. After Sales: Clustering on early defect warning system.
4. After Sales: Comparative analysis between different companies in After-Sales business.
5. After Sales: Clustering the customers and dealers in After-Sales business.
6. Connected Car: Analysis of connected car data especially weather relevant vehicle data
like temperature, sun intensity, rain and brightness to build a map layer with real-time
aggregated values which satisfies GDPR Anonymization, and provide these values to
Energy Providing Companies, which helps in better planning their energy production.
7. Connected Car: Analysis of Telematics data to prepare connected car project for
identification of relevant dealers' location based on customer driving behavior
8. Power Plants: Electricity Demand prediction for Power Plants
9. Sales: Predicting car sales and their configurations using machine learning techniques
10. Finance: Finance Margin Optimization of Trucks using machine learning techniques
11. Marketing: Analysis of customer visits to the workshop before and after recall campaign
12. Security: Developed an application for Car Theft Protection
13. Production: Digitalisation of the Production Platforms especially in Optimizing OEE
(Overall Equipment Efficiency)
14. Adhoc: Sales, Configurations and Social Media Analysis on Abgas Topic
15. Technical: Built an On-Premise based Data Lake Architecture which is implemented for 2
projects
16. Technical: Built a Cloud based Data Lake Architecture, which is implemented as
Digitalisation Platform for Cross-Functional applications. This project was implemented
with the help of Agile methods
17. Technical: Visualization of the end results of the project
18. Technical: Technology Scouting
19. Technical: Infrastructure Management
20. Technical: Data Management Support
21. Technical: Data Extraction, Transformation and Load
22. Technical: Learning New Data Technologies
23. Technical: Conducting workshops for the team members on new technologies
24. Technical: Taking Care of Technology Licenses
25. Technical: Data Security Management
26. Technical: Testing new technologies whether it is suitable for Data Lab or not and
documenting the same in internal Tech-Library
27. Technical: Data Lab Application Management
28. Technical: Installation of new technologies
? Project Profile-2:
Project Name Early Warning System for Food Supply Chain
Role Data Engineer
Organization Icomplai UG
Duration 7 months (Part-Time)
Team size 2
Environment Cloud Environment: AWS (Lambda)
(with skill versions) Database: My SQL, AWS Athena
Programming: Pl/SQL(Database), Python
O/s: Windows 10
? Project Description:
Icomplai wants to develop an early warning system for food industry by monitoring the raw
materials and provide alerts on daily basis to the customers. Icomplai is a start-up with only 2
employees, which is company founder and me. I am responsible for the complete technical tasks.
Contribution:
1. Data Extract, Transform and Load through various APIs, Web Crawling and Scraping.
Project Name Early Warning System for Food Supply Chain
Role Data Engineer
Organization Icomplai UG
Duration 7 months (Part-Time)
Team size 2
Environment Cloud Environment: AWS (Lambda)
(with skill versions) Database: My SQL, AWS Athena
Programming: Pl/SQL(Database), Python
O/s: Windows 10
? Project Description:
Icomplai wants to develop an early warning system for food industry by monitoring the raw
materials and provide alerts on daily basis to the customers. Icomplai is a start-up with only 2
employees, which is company founder and me. I am responsible for the complete technical tasks.
Contribution:
1. Data Extract, Transform and Load through various APIs, Web Crawling and Scraping.
? Project Profile-3:
Project Name MAN
Client MAN Truck and Bus Group
Role Technology Lead
Organization Infosys Technologies Limited
Duration 29 months
Team size 12
Environment Database: Oracle 9i, Oracle 11i
(with skill versions) Tools: BODS(ETL), APEX, BO(Reporting)
O/s: Windows 2000 Professional, Linux
? Project Description:
MAN Truck & Bus Group plans to improve quality monitoring and control of individual areas. The
objective of this project is to increase transparency with regard to quality targets and quality
achievement. It is implemented within the scope of the Integrated Data Warehouse (IWH) of
MAN.
Contribution:
1. Development of an application for predictive maintenance in repairs
2. Analyzing raw data, drawing conclusions & developing recommendations
3. Architecture Design
4. Onsite Coordinatinator (Germany) between Customer (MAN Germany) and Offshore
Team (Infosys India)
5. Creation of APEX applications
6. Database Monitoring
7. Migration of the Database
8. Responsible for the Database Maintenance
9. Database Cleanup
10. Creation and execution of the Jobs in Oracle, BODS and Linux
11. Responsible for all Database activities.
12. Communication to the coordinators and to the Downstream.
13. Answered Business users for Adhoc requests.
14. Data reconciliation across multiple databases.
Project Name MAN
Client MAN Truck and Bus Group
Role Technology Lead
Organization Infosys Technologies Limited
Duration 29 months
Team size 12
Environment Database: Oracle 9i, Oracle 11i
(with skill versions) Tools: BODS(ETL), APEX, BO(Reporting)
O/s: Windows 2000 Professional, Linux
? Project Description:
MAN Truck & Bus Group plans to improve quality monitoring and control of individual areas. The
objective of this project is to increase transparency with regard to quality targets and quality
achievement. It is implemented within the scope of the Integrated Data Warehouse (IWH) of
MAN.
Contribution:
1. Development of an application for predictive maintenance in repairs
2. Analyzing raw data, drawing conclusions & developing recommendations
3. Architecture Design
4. Onsite Coordinatinator (Germany) between Customer (MAN Germany) and Offshore
Team (Infosys India)
5. Creation of APEX applications
6. Database Monitoring
7. Migration of the Database
8. Responsible for the Database Maintenance
9. Database Cleanup
10. Creation and execution of the Jobs in Oracle, BODS and Linux
11. Responsible for all Database activities.
12. Communication to the coordinators and to the Downstream.
13. Answered Business users for Adhoc requests.
14. Data reconciliation across multiple databases.