Skill Profile

Data Visualization

This skill defines expectations across roles and levels.

Data Engineering Data Visualization

Roles

1

where this skill appears

Levels

5

structured growth path

Mandatory requirements

0

the other 5 optional

Domain

Data Engineering

Group

Data Visualization

Last updated

2/22/2026

How to Use

Choose your current level and compare expectations. The items below show what to cover to advance to the next level.

What is Expected at Each Level

The table shows how skill depth grows from Junior to Principal. Click a row to see details.

Role Required Description
Data Scientist Creates basic visualizations via matplotlib and seaborn: histograms, scatter plots, box plots, heatmaps. Visualizes feature distributions and correlations for EDA. Builds model metric charts: ROC curve, confusion matrix.
Role Required Description
Data Scientist Creates interactive visualizations via Plotly and Altair for data exploration. Builds informative dashboards in Streamlit for communicating results to stakeholders. Visualizes experiment and A/B test results with confidence intervals.
Role Required Description
Data Scientist Designs visualizations for explaining complex ML models: SHAP plots, partial dependence plots, attention maps. Creates custom visualizations for high-dimensional data via t-SNE/UMAP. Establishes visualization standards for the data science team.
Role Required Description
Data Scientist Defines data and ML results visualization standards for the organization. Establishes report templates for different stakeholders: technical, product, business. Coordinates creation of self-service analytics dashboards.
Role Required Description
Data Scientist Shapes data visualization strategy at organizational level. Defines tools and platforms for ML results visualization. Influences data-driven decision culture through visual communication quality.

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