Murilo Miranda

• Built end-to-end medallion architecture (Bronze→Silver→Gold) in Databricks: real estate APIs → PySpark cleansing & deduplication → dimensional modeling → Power BI dashboards. • Orchestrated Azure Data Factory & Databricks Workflows with validation, error handling, and alerting, reducing downtime. • Integrated SQL Server, Excel, APIs, cloud storage. • Used Git, RLS, SLA-backed stakeholder collaboration. • Documented lineage & tuned PySpark performance.

Migrated production web app from Vaadin 8 to Vaadin 23: managed dependencies, breaking changes, and refactored legacy components. Used Maven, Spring Boot, Git/GitLab. Applied best practices: version control, reproducible builds, structured project management.

Built reproducible R pipelines for ecological data from agricultural landscapes. Applied spatial statistics & GIS (ArcGIS, variograms, autocorrelation) to quantify land use change impacts on moth populations. Maintained ecosystem services DB with ETL & validation. Used ANOVA, regression, feature selection for peer-reviewed publications. Collaborated with researchers to translate biological questions into testable workflows.

Developed an R package for maximum likelihood estimation of species abundance distributions. Implemented model comparison (AIC, likelihood ratio tests) and optimization routines, improving efficiency & reproducibility. Wrangled ecological datasets for MLE fitting. Wrote clean, documented, version-controlled code following research software best practices.

Earned IHK “Fachinformatiker Anwendungs­entwicklung” certification through structured vocational program. Training covered software project planning, algorithms, IT system implementation. Hands-on experience with Java, Spring Boot, SQL, Git. Team projects with version control, documentation, code reviews. Understood full SDLC from requirements to deployment. Built OOP, data structures, and DB design foundations supporting current data engineering work.

Investigated macro-moth biodiversity changes along ecological succession and agricultural land-use gradients. Applied GLM, ANOVA, ArcGIS, and time-series forecasting. Built reproducible R pipelines from raw data to statistical outputs. Performed spatial autocorrelation analysis to quantify land-use impacts. Research published in peer-reviewed journals.

Researched agent-based modeling and complex networks in ant colony interaction dynamics. Designed theoretical models with adjacency matrices for simulation. Performed network analysis on simulation outputs to study individual roles and colony structures. Skills: mathematical modeling, statistical computing (R), reproducible workflows. Foundation in systems thinking and computational modeling applicable to data engineering.

Studied plant-pollinator interactions and ecological succession through field research. Collected environmental data, performed statistical analysis, and applied data cleaning, transformation, and visualization to field observations. Developed skills in hypothesis testing, data quality, documentation, and reproducible methods, core principles now applied to data engineering and analytics workflows.