Michal Bonino

I am an experienced Data Architect and workflow optimizer with deep expertise in designing, governing, and operationalizing enterprise‑scale data ecosystems. I bring a blend of technical mastery, systems thinking, and business alignment, enabling organizations to transform fragmented data into reliable, governed, analytics‑ready assets.

I specialize in

Modern data architecture frameworks including Data Vault, Data Fabric, and Data Mesh

Financial data repositories, regulatory data flows, and high‑integrity data lineage

Microsoft Azure data services across ingestion, orchestration, storage, and governance

Data observability, quality frameworks, and metadata‑driven automation

Workflow optimization, process redesign, and automation using tools like Selenium, Playwright, and AutoHotkey

My approach

PROFESSIONAL SUMMARY

• Senior Database Architect and Modeler with a M.S. in Information Science and 20+ years of technical expertise regarding data models, database design development, data mining and segmentation techniques.
• Ability to identify current-and-future-state business processes and helping the business stakeholders envision the future by analyzing business requirements, designing/modifying system processes to meet the analytical capability needs.
• Well versed with data warehousing concepts and its design by using star and snowflake schema methodologies as well as an understanding of the Data Vault (DW 2.0), Ontologies and Semantic Models.
• Responsible for preparation of source to target mappings through an integrated, streamlined, and productive paring of a variety of industry-standard data tools, automation techniques and automatic documentation.
• Strong track record of architecting and implementing complex solutions using data migration and data integration tools such as Informatica Power Center and IBM Infosphere Suite.
• Hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, and ETL and data ingestion protocols). 
• Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required. 
• Good knowledge of Data warehousing concepts, metadata management, data modeling, and related tools (Erwin or ER Studio or others) required. 
• Experience in Python and AWS. 
• Experience in Performance Tuning and PL/SQL. 
• Experience in Oracle, SQL Server, MySQL and Postgres. 
• Experience in QA testing, Diagraming, Design Build and Maintain Infrastructure.

EDUCATION/ CERTIFICATIONS

• MS, Information Science, University of Pittsburgh - School of Information Sciences
• B.A., Economics, University of Pittsburgh
• CompTIA Security+, Issued March 2019, Renewed 2022
• IEEE Certificate in Software Project Management
• IEEE Certificate in Software Development