Roles in data analytics
A data analyst can't answer the VP's sales question alone. They're one part of a larger data team that builds and maintains a data estate to serve analytics. Each role owns a specific part of the process, and knowing those boundaries helps you focus your work and collaborate with the right people.
Your organization might combine these roles or use different titles, but the responsibilities remain consistent.
Data engineer
At Tailwind Traders, a data engineer builds the pipeline that pulls daily sales transactions from the point-of-sale system, the e-commerce platform, and the marketing database. They standardize date formats, unify product IDs across systems, and load the combined data into a lakehouse every morning.
Data engineers build and maintain the infrastructure that moves data from source systems into formats ready for analysis. When an analyst connects to a source and finds clean, unified, timely data waiting, data engineering made that possible.
Analytics engineer
The analytics team at Tailwind Traders discovered that "revenue" meant different things in different reports - one included returns, another didn't. An analytics engineer resolves this discrepancy by defining "net revenue" as "gross sales minus returns and discounts" and building that definition into a certified semantic model that every team's report uses.
Analytics engineers bridge data engineering and analysis. They combine business context with data modeling expertise to create reusable, trustworthy data assets that ensure consistent definitions across the organization.
Data analyst
With clean data in a certified model, a data analyst at Tailwind Traders builds the interactive dashboard that shows the VP sales performance by channel and product. They choose the right visualizations, implement row-level security so regional managers see only their data, and schedule daily refreshes.
Data analysts turn data into reports and visualizations that others use to make decisions. Their value is validating the output directly addresses what stakeholders need to know.
Data scientist
To build the revenue forecast, a data scientist at Tailwind Traders trains a time-series model on three years of sales data, incorporating seasonality and promotional events. The model produces monthly revenue predictions that the data analyst then visualizes in the VP's dashboard.
Data scientists perform advanced analytics beyond standard reporting. They build machine learning models, identify hidden patterns, and generate predictions that inform strategic decisions. A data scientist's work often feeds back into the analytics process as scores or predictions that analysts visualize.
Business analyst
The VP's operations manager, acting as a business analyst, defines the original question and the KPIs that matter: sales by channel, close rates by product, and pricing impact on margins. After the analytics team delivers the dashboard and pricing analysis, the business analyst interprets the findings and recommends that leadership adjust the pricing strategy to optimize the balance between deal volume and margin.
Business analysts focus on interpreting data in the context of business strategy. They define what questions need answers, identify the KPIs that matter, and translate insights into recommendations that leadership can act on.
Data team collaboration
No role works in isolation. Here's how the five roles connect at Tailwind Traders to answer the VP's question:
| Role | At Tailwind Traders | Primary responsibility |
|---|---|---|
| Data engineer | Builds pipeline from POS, e-commerce, and marketing systems | Moves data from sources into analysis-ready formats |
| Analytics engineer | Defines "net revenue" in a certified semantic model | Ensures consistent definitions across the organization |
| Data analyst | Builds the VP's sales performance dashboard | Delivers output that addresses what stakeholders need to know |
| Data scientist | Trains revenue forecast on three years of sales data | Feeds predictions back into the analytics process |
| Business analyst | Recommends adjusting pricing strategy based on findings | Translates insights into recommendations leadership can act on |
Each role's output becomes the next role's input. When one link is missing, downstream roles feel it directly.
Tip
Which of these roles exist in your organization? Are any responsibilities handled by a different role than described here?