Technical Skills
Languages, Platforms, Tools, and the Ability to Keep Learning
Over the years, my toolkit has grown from classic geospatial and desktop analysis tools into modern data platforms, cloud workflows, machine learning frameworks, application development, and deployment environments.
I value strong technical foundations, but I also value adaptability. The tools matter. The ability to learn new ones quickly matters just as much.
A Broad and Evolving Toolkit
My technical background spans geospatial analysis, data science, engineering, automation, machine learning, reporting, and application development. Over time, that has included everything from ArcGIS, Visual Basic, and Excel to Python, R, SQL, Databricks, cloud platforms, and modern machine learning frameworks.
I tend to pick up tools in service of solving real problems. That means I am less attached to any one platform than I am to understanding what the problem requires and choosing the right approach. I am comfortable working with the technologies I know well, and equally comfortable ramping up on adjacent tools when the situation calls for it.
I do not just like learning new tools. I like getting good enough with them to build something useful.
Languages & Querying
Python
My most flexible language for application development, automation, analytics, machine learning, APIs, scripting, and general problem solving.
R
Strong experience in analytics, modelling, data manipulation, and Shiny application development for user-facing tools.
SQL
Extensive experience working across relational and analytical systems, including MySQL, PostgreSQL, SQL Server, Spark SQL, and Databricks SQL.
Data, Cloud, and Development Environments
Databricks
Deep experience with notebooks, jobs, pipelines, MLflow, Delta Lake, Databricks SQL, medallion architecture, Apps, and governed analytics environments.
AWS
Experience working with cloud-hosted data and application workflows, along with the supporting mindset needed for scalable modern architecture.
Snowflake
Currently building deeper experience here as a complementary platform, with the expectation that it will be increasingly useful across modern analytics environments.
Modelling & AI Tools
Regression & Forecasting
Experience using modelling techniques to support planning, prediction, and structured analysis.
Tree-Based Models
Experience with approaches such as random forest and gradient boosting for predictive analytics and decision support.
TensorFlow & PyTorch
Experience building and testing neural network models in modern deep learning frameworks.
AI-Assisted Development
Active interest in using modern AI tools to accelerate development, experimentation, and problem solving.
Applications, Interfaces, and Deployment
I have built and deployed applications in multiple environments, including RStudio Connect, Databricks Apps, Shiny, Flask, and other custom application frameworks. I enjoy building tools that put data and analytics directly into the hands of users, especially when the interface makes a complex process feel simple and approachable.
I am comfortable working across backend logic, data access, user-facing interfaces, and the practical realities of deployment.
Version Control and Technical Workflow
I use Git extensively for both professional and personal projects and have worked with GitLab, GitHub, and Bitbucket. I value clean version control practices because they make collaboration, experimentation, and long-term maintainability much easier.
I am also comfortable with the broader workflow around technical development, including debugging, iterative improvement, structured experimentation, and adapting to the needs of a project as it evolves.
Other Technologies in the Mix
ArcGIS
A core part of my earlier geospatial foundation and still an important part of how I think about spatial problem solving.
Excel & Visual Basic
Part of the practical toolkit that shaped my approach early on: solve the problem in front of you with the tools available.
C#
Some prior experience here, enough to be comfortable reading, understanding, and re-engaging when needed.
Databases & Data Access
Experience working directly with structured data across multiple database platforms, connectors, and management tools such as DBeaver.
What Matters Most Technically
Technical breadth matters because it gives me options. It lets me choose tools intentionally, move across domains more easily, and connect pieces of a system that might otherwise remain isolated. But what matters most is not simply knowing a long list of technologies. It is being able to understand a problem, evaluate tradeoffs, and use the right tools to build something that works.
The strongest technical skill I bring may be that I am not afraid to learn what I do not yet know, and I usually learn it quickly when there is something worth building on the other side.
My toolkit has changed many times over the years. Curiosity, adaptability, and practical problem solving have remained constant.
Brett Wiens 