Code for Geniuses

Roles guide

What do data people do?

Six professions, explained without jargon: what they do on a normal day, which tools they work with and what you can practice here to get closer to each one.

Quick quiz · 3 questions

What appeals to you most?

Question 1 of 3

🔎

Data analyst

Turns business questions into queries and answers into decisions.

A typical day

  • •Receives questions like “why did sales drop in March?”
  • •Writes SQL queries to pull the data that's needed
  • •Cleans, summarizes and compares results
  • •Presents conclusions with clear tables and charts

Tools

  • SQL
  • Excel or Google Sheets
  • A dashboard tool (Power BI, Looker, Tableau…)

Practice it here

🦉 Practice explaining every result in one sentence: the “so what?” is as important as the query.

📊

Business analyst (BI)

Builds the reports and dashboards the team looks at every week.

A typical day

  • •Defines metrics with the team (sales, sign-ups, retention…)
  • •Prepares summary tables and dashboards that update themselves
  • •Spots odd changes and raises the alarm in time
  • •Translates business needs into data requirements

Tools

  • Advanced Excel
  • SQL
  • Power BI, Looker Studio or similar

Practice it here

🦉 Learn to design a good dashboard: few numbers, well chosen, with context.

🧱

Analytics engineer

Organizes data into clean, reliable tables so others can analyze it.

A typical day

  • •Writes SQL transformations that turn raw data into useful tables
  • •Documents what each column means
  • •Adds tests to catch duplicate or empty data
  • •Reviews other people's SQL

Tools

  • SQL (a lot)
  • dbt or similar tools
  • Git
  • A cloud data warehouse

Practice it here

🦉 Master JOINs and CTEs (WITH): they are the bread and butter of this role.

⚙️

Data engineer

Builds the pipelines that move data from one system to another.

A typical day

  • •Connects data sources (apps, APIs, files) to the warehouse
  • •Schedules automatic loads and makes sure they don't fail
  • •Optimizes queries and large tables
  • •Looks after data security and permissions

Tools

  • SQL
  • Python
  • Orchestrators (Airflow, Dagster…)
  • Cloud services

Practice it here

🦉 After SQL, learn Python: it's the second essential tool of the role.

🧪

Data scientist

Uses statistics and models to predict, classify and experiment.

A typical day

  • •Explores data to find patterns
  • •Designs experiments (for example, A/B tests)
  • •Trains and evaluates predictive models
  • •Explains the results to non-technical people

Tools

  • SQL
  • Python or R
  • Statistics
  • Notebooks (Jupyter)

Practice it here

🦉 Basic statistics (means, spread, correlation) will give you an edge from the start.

💼

Financial or operations analyst

Lives in the spreadsheet: budgets, forecasts and cost control.

A typical day

  • •Maintains budget and forecast models
  • •Reconciles figures from different sources
  • •Prepares monthly reports with pivot tables and charts
  • •Spots variances and proposes adjustments

Tools

  • Advanced Excel
  • Basic SQL
  • Accounting tools or ERP

Practice it here

🦉 Combine Excel with some SQL: pulling the data yourself will make you much faster.