Data Analyst → Analytics Engineer | Business Intelligence | AI Explorer

I'm a Data Analyst moving into Analytics Engineering, currently working as a Digital Analyst on Mercedes-Benz.io's Central Operations Services project. I thrive at the intersection of data modeling, KPI definition, and technology I thrive at the intersection of data modeling, KPI definition, and technology — turning raw data into governed, reliable, and actionable products. With a background in Power BI, SQL, Python, and financial data governance, I bring both technical depth and financial acumen to every project.

Currently completing a Master's in Business Analytics & AI at Porto Business School, and building AI Agents that go beyond static dashboards — systems that reason, act, and explain.

• Current Role: Digital Data Analyst (Consultant) at Aubay, on the Mercedes-Benz.io Central Operations Services project (August 2026)
• Previous Role: Data Analyst (Consultant) at Natixis BPCE via Axco CMG (Porto, PT) — Data Management & AI Team, Finance Department
• Focus Areas: Analytics Engineering, Data Modeling, ETL/ELT, Business Intelligence, KPI Definition, Data Governance for Finance
• Currently exploring: AI Agents, LLMs, Data Engineering, and how analytics engineering practices are reshaping financial data management
• Tools & Technologies: SQL, Python, Fabrics, Power BI, dbt, Databricks, BigQuery/GCP, OpenAI API & Agents framework, Streamlit, SAP ERP, Salesforce, AWS, Microsoft Power Automate/Power Apps
• Languages: Spanish (Native), English (Advanced), Portuguese (Intermediate)

• Business Analytics and AI — Executive Master, Porto Business School (January 2026 – Ongoing)
• Data Analytics Bootcamp — allWomen (2025)
• Double Master's Degree in Accounting & Finance — EAE Business School & Universidad Rey Juan Carlos (2024)
• Certifications from Google, Coursera, DataCamp, Microsoft (incl. DP-600, NASBA, Code First Girls, and more

• Building AI Agents — conversational data analysts that query real datasets, reason about results, and deliver insights in plain English, using the OpenAI Agents framework and the Claude API, deployed on Streamlit.
• Analytics engineering fundamentals — modeling data with dbt, building on Databricks and BigQuery, and moving from dashboard-building toward end-to-end data products.
• Data Governance for Finance — applying frameworks and best practices for financial data management, most recently at Natixis BPCE and now at Mercedes-Benz.io.
• Automating reporting processes, defining KPIs, and improving data pipelines.

A conversational AI data analyst built on Claude (Anthropic) that queries 101,596 rows of global food production and climate data. Ask it anything in plain English — it reasons, uses tools, and delivers insights.

• Live app: food-climate-ai-agent.streamlit.app
• Stack: Python · Claude API · Pandas · Streamlit · GitHub
• Built on top of: Food & Climate Data-Driven Sustainability (original bootcamp project)

• LinkedIn
• Twitter
• Email: ivanaloveraruiz@gmail.com
• Porto, Portugal

Languages:     SQL · Python · R · DAX
Analytics Eng: dbt · Data Modeling · ETL/ELT · Databricks · BigQuery · Fabrics
AI & LLMs:     OpenAI Agents Framework · Claude API · Prompt Engineering · LLM Integration
Tools:         Power BI · Streamlit · SAP · Excel (Power Query) · Looker Studio
               Salesforce · Google Cloud · Fabrics
               Microsoft Power Automate · Microsoft Power Apps
Methodologies: Data Governance · Data Viz · Data Cleaning · Financial Modeling
               Agile/Scrum · Project Management · AI Agent Development