Open to opportunities

Milena Dilly

@milenadilly

Message

I turn complex data into trusted business decisions and automated workflows.

Brazil

Message

What I'm looking for

I'm looking to apply data analytics, AI agents, and workflow automation to reduce manual work, create trusted business metrics, and help teams make faster, better decisions.

At Dillemburg Eletro Comercial, I built a centralized data layer and automated end-to-end pipelines, reducing manual reporting effort by over 70% and improving sales forecasting accuracy by approximately 25%.

Over 10+ years across data and marketing analytics, I've used SQL, Python, dbt, BigQuery, Power BI, and Looker to standardize KPIs, unify disconnected systems, and help commercial, finance, and operational teams act on reliable data. I'm now applying that same outcome-focused approach to AI agents and automated workflows that reduce manual work and speed up decision-making.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Analyst

Current

Dillemburg Eletro Comercial

Jun 2024 - Present (2 years 2 months)

Dillemburg is a reference company in the electrical and hydraulic materials industry in South of Brazil.

• Commercial and finance teams were making decisions off inconsistent, hard-to-trust numbers scattered across systems — I built a centralized data layer with standardized business metrics, giving leadership one trusted source for revenue and performance data
• Reporting was consuming hours of

SQL Data Modeling Data Validation Analytics Engineering Data Documentation Looker Workflow Automation Data Governance ELT Data Quality Data Pipelines Revenue Analysis data transformation Data Engineering Data Build Tool (Dbt)Git Python DBT

Data Analyst

Dillemburg Eletro Comercial

Feb 2018 - May 2024 (6 years 3 months)

• Business metrics varied depending on who pulled the report — I built analytical datasets and standardized definitions, increasing the reliability of the numbers used across multiple departments
• Recurring reports ate up hours that could go into actual analysis — I automated them with Python and SQL, accelerating access to operational and commercial insights
• Performance reviews were slow and i

SQL Forecasting Data Validation Data Documentation Looker KPI Reporting Data Governance ELT Data Quality Python Revenue Analysis Power BI Business Process Improvement Data Analytics Git

Marketing Analyst

Wizard by Pearson

Mar 2015 - Jan 2018 (2 years 10 months)

Wizard by Pearson is a global leader in language education.

• Marketing spend wasn't clearly tied to which campaigns actually converted — I analyzed performance and funnel data, identifying opportunities that contributed to a ~30% increase in qualified lead performance
• Reporting on campaign results was manual and slow — I automated it with Python and Excel, improving visibility into campaign p