Summary
Results-driven data professional with a consulting background, specializing in data engineering and enterprise-scale automation within the Microsoft Azure and Fabric ecosystems. Expertise in architecting high-performance data pipelines, custom orchestration engines, and advanced semantic modeling. Microsoft certified across Fabric (Data/Analytics Engineering), Azure Data Engineering, and Power BI.
Experience
Improving | Winnipeg, MB
- Architected and open-sourced a Fabric Orchestrator Python toolkit featuring an async REST API client, MCP server with 20+ AI-agent tools, refresh orchestration engine with parallel execution and dependency management, and a terminal UI for real-time monitoring.
- Built a Power BI Report Dependency Analyzer - a Python engine that parses PBIR report definitions to extract measure/column lineage, with CLI subcommands, MCP tools for LLM integration, cross-model impact analysis identifying dead/shared/orphaned measures, and semantic model diffing with normalization. Backed by 100+ unit tests.
- Developed centralized Power BI Semantic Models and Dataflows shared across multiple cross-functional teams, establishing a single source of truth for enterprise metrics and reducing data model duplication.
- Created executive-level Power BI dashboards providing visibility into KPIs across operations, supply chain, and demand planning, allowing data-driven decisions to be made.
- Designed and implemented scalable data pipelines using Azure Data Factory and Fabric dataflows to ingest, transform, and load data from diverse sources (OLTP databases, REST APIs, Snowflake, PostgreSQL, Azure SQL Server).
- Built and managed Fabric Lakehouses (Delta/External tables), Spark notebooks, and Azure SQL Databases for analytical workloads, with automated deployments via Azure DevOps.
- Standardized Power BI version control practices using Git, authored internal documentation with MkDocs, and developed and delivered CI/CD training sessions demonstrating Git-integrated Power BI development workflows.
- Authored custom visuals in Power BI using SVGs and Vega, and performed ad-hoc analyses on large datasets using DuckDB and Bash scripting.
Ultracuts | Winnipeg, MB
- Automated monthly financial reporting across 30+ salons by building a solution to ingest sales data from multiple sources, process complex transactions (payments, discounts, promotions), and generate journal entries - reducing processing time by approximately 16 hours per month.
- Developed VBA macros and Power Query solutions for automated raw data cleaning, enhancing accuracy and saving time.
- Utilized Python scripts to automate data extraction from unstructured files.
- Collaborated with peers to identify reporting needs and develop solutions that addressed specific business challenges.
Certifications
Education
Business Administration, Statistics and Management Information Systems
Skills
Data Engineering
Microsoft Fabric, Databricks, Power BI, Azure Synapse, Azure Data Factory, Azure SQL, Azure Data Lake, Spark, Azure Analysis Services, Azure Functions, Data Pipelines, Cloud Data Warehousing, ETL/ELT Architecture, Delta Tables, Lakehouse
Data Visualization
Power BI, Matplotlib, Seaborn, Plotly, Jupyter Notebooks, Streamlit
Programming
Python, SQL, PySpark, DAX, Power Query M, Bash
Databases
Azure SQL, SQL Server, DuckDB, PostgreSQL, MySQL
Other Tools
Git, Docker, Linux