Microsoft Certified: Power BI Data Analyst Associate (PL-300)

• Designed a future-proof client database for marketing purposes
• Analyzed requirements, designed, and modeled an entity-relationship model
• Consolidated and optimized a client file from various data sources for targeted marketing campaigns
• Worked closely with marketing and IT in an agile environment to iteratively develop the solution
• Technologies and methods: MS Office (mainly Excel), MS Dynamics CRM, MS SharePoint

Tasks: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.

Activities:

• Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
• Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
• Developed automated data pipelines with Python, dbt, and GCP services for different data sources
• Built monitoring and alerting systems for real-time platform monitoring
• Implemented data versioning and quality checks at every layer
• Designed automated test and deployment pipelines in GitLab and Bitbucket

Achievements:

• 2× production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
• Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, configuration errors to 0
• Delivered a complete end-to-end data platform at ~€10/month infrastructure cost
• Migrated 7 database tables with 0 downstream issues
• Removed 100% exposed credentials, eliminated external vendor dependency
• Delivered integration of 3 teams in 1 sprint

• Analysis of complex business processes and end-to-end user journeys in digital product and platform environments
• Gathering, structuring, and prioritizing business and technical requirements (Functional / Non-Functional Requirements)
• Translating business goals into actionable requirements, user stories, and acceptance criteria
• Conducting stakeholder interviews, workshops, and reviews with business teams, IT, UX, and management
• Creating and maintaining requirement artifacts (BRD, FRD, user stories, process models, decision papers)
• Ensuring consistency between business needs, technical implementation, and product vision
• Close collaboration with development teams to clarify business questions during implementation
• Support with impact analyses (A/B tests), change requests, and scope management
• Quality assurance of implemented requirements including acceptance criteria and business testing
• Advising on the further development of product strategy and roadmap structure
• Prioritizing backlog items based on business value
• Defining and sharpening product goals, KPIs, MVP definition, and other success metrics
• Evaluating new features, tools, and initiatives from a user and business perspective
• Facilitating decision-making between business, product, and technology
• Supporting go-to-market considerations and product positioning
• Sparring partner for product and stakeholder decisions at management level
• Dashboard creation, data modeling, BI report administration, and data analysis in Power BI

• KPI dashboards for inventory and goods received quality control & testing ETL, dataset, dataflows and report development, complex DAX solutions

Data sources: Dataverse, RDB, Excel

Tools: ETL, data modeling, data flows, Power Query, M, Power BI, complex DAX

• Capacity: 25%

• Completed an intensive AI Engineering Program focused on LLM evaluation, retrieval, agent orchestration, and multimodal workflows.
• Designed retrieval pipelines with document ingestion, semantic search, and citation-aware outputs using LangChain and ChromaDB.
• Built LangGraph-based agent workflows with state handling, clarification loops, and human-in-the-loop approval steps.
• Applied prompt engineering and evaluation patterns, including scoring logic and guardrails, to improve output quality and reliability.
• Worked extensively with Python, FastAPI, OpenAI APIs, LangChain, LangGraph, and ChromaDB in end-to-end implementations.

• Analysis of process data
• Data preparation with SQL
• Development of reports & dashboards in Celonis

• Redesigned org model &led exec workshops for global sales organization of 200+ people
• Facilitated cross-functional enablement sessions and training for 100+ global sales and strategy teams
• Led internal coaching & mentoring circles for 30+ colleagues across functions and capabilities
• Designed and implemented GTM programs to boost tooling adoption and upskill customer-facing teams

• Designed and evaluated high-quality prompts and completions for Large Language Models (LLMs), focusing on improving response accuracy, instruction-following behavior, and factual consistency.
• Annotated and rated LLM-generated outputs for grammar, coherence, relevance, and truthfulness.
• Developed RLHF-style preference data by ranking model completions to inform reinforcement learning fine-tuning cycles.
• Participated in prompt engineering experiments to assess the effect of instruction format, verbosity, and phrasing on model behavior.
• Conducted error analysis and quality assurance on large-scale NLP datasets, identifying edge cases and linguistic ambiguity affecting LLM performance.

• Data management & analysis of data from leading e-commerce companies
• Requirement gathering
• Visualization (reports and dashboards) of accounting and business data
• Digitalization and automation of accounting and tax processes
• Data modelling and analysis

• In-depth forensics of old and new data sources
• Enhancing existing reports and creating new data analyses
• Data preparation from source systems and semantic models
• Azure DevOps integration
• Tools/Skills: MS-PowerBI, DAX, MS-Office 365, PowerQuery, M, PowerAutomate, Redmine, SharePoint, SQL (T-SQL, Oracle), MS Fabric

• Applied Large Language Models for text classification and definition detection.
• Designed ETL pipelines and dashboards for data analysis through SQL, Power BI, and Python.
• Contributed to academic publications and data visualization for AI projects using PyTorch and TensorFlow.
• Bridged technical and business teams to drive data-driven decision-making.

• Implemented source code management for existing databases using SSDT and Bitbucket
• Implemented continuous integration pipelines with Azure DevOps
• Supported implementation of user stories (T-SQL and VBA) for existing database systems