Mag. Bogdan Las.

Aufbau des DWH und Reportingsysteme ·Entwicklung in Python von ETL-Pipelines für Reporting ·Erstellen Berichte in Tableau ·Entwerfen von technischen Datenbankmodellen in Data Vault ·Automatisierung interner Prozesse: Einführung von automatisierten CI/CD, Python/SQL Testen in die Produktionsumgebung. ·Organisation der Migration von Daten von Azure (Microsoft SQL-Server) zum Snowflake ·Planen einer Architektur und Implementieren eines Testsystems für Fachanwender zur Einhaltung hoher Datenqualitätsstandards

· Entwicklung von ETL-Pipelines für Meldewesensysteme.Beschleunigung der gesamten täglichen Ladezeit um bis zu 40% · Mitarbeit an Digitalisierungsprojekten der Bank (Spezifikation der Architektur von ETL-, Data Lake- und DWH-Systemen). · Automatisierung interner Prozesse: Einführung von automatisierten CI/CD, Testen in die Produktionsumgebung. Technologie-Stack: Java, DataStage, Oracle DB, PL/SQL, PowerShell Tools: Bitbucket, Jira, Confluence

· Implementierung von komplexen Datenintegrationsprozessen auf Basis moderner ETL-Frameworks in Informatica; · Entwerfen von technischen Datenbankmodellen auf der Basis verschiedener Modellierungsparadigmen (3NF, Data Vault, Star, ...); · Co-Design von kundenspezifischen Frameworks innerhalb der eingesetzten ETL-Tools; · Automatisierung von Datenqualitätstests für ETL-Pipelines (PL/SQL, Bash, Jenkins). Technologie-Stack: Python, Informatica, DB2, PL/SQL, Unix (AIX) & bash Tools: Gerrit, Jira, Confluence

Project: Data analysis of financial trade data. Working with Vertica DB, Python for parallel data computing (Python multiprocessing, Dask. Analyze business requirements to the trading data, Detection data outlines/quality problems. Writing ETL processes for providing proper trade data, write alert events, visualize data sanity check. Personal achievement: rewrote ETL scenario to speed it up from 11 processing hours to 45 minutes.

Project: I was working on different tasks like creating models that should pick up most suitable audiences for internet marketing companies. It means I was forming different machine learning models aimed at client retention, fraud detection, and client conversion increase. Main achievement: create a micro-service for providing regular datasets for constantly self-learning NLP machine learning algorithm of providing a smart news feed.

Responsibilities: • Working in a SCRUM team as a system analyst; • Review high level business requirements coming from on-site domain team; • Feed the detailed specifications into the team prior to every iteration; • Helping with understanding of requirements; • Act as a domain expert for developers and testers within the SCRUM team; • Managing financial reports, data visualization via internal ERP system; Technology stack: BPMN, Highcharts JS, MS SQL, PHP, Python

Responsibilities: • Configuring Windows Server, Ubuntu Server (Web services, XMPP-chat, VPN • Adjustment of the cloud system EDI (OwnCloud / Nextcloud + onlyoffice document server) • Writing software to automate the formation of physical advertising mailings • Maintaining backups and reservation Technology stack: Docker, Linux, nginx, openssl

Forschungseminar Hauptseminar: Process Discovery — Algorithmen Betriebliches Wissensmanagement / Wissensbasierte Systeme Informationsverarbeitung im Handel und elektr. Märkte IT-Architektur und Integrationsmanagement Programmierparadigmen der künstlichen Intelligenz Informationsmanagement

Decision-making theory; System theory and system analysis; Econometrics - advanced level; Enterprise architecture; Information security management; information business analysis; Financial reporting analysis; International standards of business analytics and business process modeling

Analysis and Modeling of Business Processes; Data visualization, analysis; Simulation Modelling; IT architecture; Information management; Project Management Automation; Databases; Linear Algebra Mathematical Methods of Operations Research Mathematical Analysis