Data Roles: DBA, Engineer & Analyst
Data doesn't manage itself. Meet the three key roles that keep data flowing — the database administrator, data engineer, and data analyst.
Who works with data?
Think of data like water in a city.
The data engineer builds the pipes and pumps — they design the infrastructure that moves data from where it’s created to where it’s needed.
The database administrator (DBA) maintains the reservoirs — they keep databases running, secure, backed up, and performing well.
The data analyst is the person who turns on the tap and uses the water — they query data, build reports, and turn raw numbers into insights for decision-makers.
The three data roles
Database Administrator (DBA)
The DBA is the guardian of the database. They keep it running, secure, and recoverable.
Jake IS a DBA at CloudPulse. His daily responsibilities:
| Responsibility | What Jake Actually Does |
|---|---|
| Manage databases | Provisions Azure SQL databases, configures settings, monitors health |
| Security | Sets up user permissions, configures firewall rules, enables encryption |
| Backup & recovery | Configures automated backups, tests restore procedures, plans disaster recovery |
| Performance tuning | Identifies slow queries, creates indexes, adjusts resource allocation |
| Availability | Ensures databases are online 24/7, sets up failover groups |
| Patching & updates | Applies security patches, plans maintenance windows |
Key tools: Azure SQL Database management tools, Azure portal, SQL Server Management Studio (SSMS)
Data Engineer
The data engineer is the builder of pipelines. They design the systems that move data from source to destination.
At FreshMart, the data engineering team builds the infrastructure that feeds Priya’s dashboards:
| Responsibility | What the Engineering Team Does |
|---|---|
| Build data pipelines | Create ETL/ELT processes that extract data from POS systems, clean it, and load it into the warehouse |
| Design data architecture | Choose between data lakes, warehouses, and lakehouses — plan how data flows through the organisation |
| Ensure data quality | Validate data, handle missing values, enforce standards across sources |
| Manage data platforms | Set up and maintain Microsoft Fabric, Azure Databricks, or Azure Data Factory |
| Optimise for scale | Design systems that handle growing data volumes without breaking |
| Security & compliance | Implement data governance, manage access to sensitive data in pipelines |
Key tools: Microsoft Fabric, Azure Data Factory, Azure Databricks, Apache Spark, Python, SQL
Data Analyst
The data analyst is the storyteller. They turn raw data into insights that drive business decisions.
Priya IS a data analyst at FreshMart. Her responsibilities:
| Responsibility | What Priya Actually Does |
|---|---|
| Explore data | Queries the data warehouse to understand patterns and anomalies |
| Build reports & dashboards | Creates Power BI reports showing sales trends, inventory levels, store performance |
| Data modelling | Designs star schemas, creates measures and calculated columns in Power BI |
| Visualise insights | Chooses the right charts and visuals to communicate findings clearly |
| Collaborate with stakeholders | Works with store managers to understand what data they need for decisions |
| Monitor KPIs | Tracks key metrics and sets up alerts when numbers go outside expected ranges |
Key tools: Power BI, Excel, SQL, Microsoft Fabric (for querying)
| Feature | DBA | Data Engineer | Data Analyst |
|---|---|---|---|
| Focus | Database health & security | Data pipelines & infrastructure | Insights & reporting |
| Works with | Operational databases | Data lakes, warehouses, pipelines | Reports, dashboards, models |
| Key question | 'Is the database running well?' | 'How does data get from A to B?' | 'What does the data tell us?' |
| Primary tools | SSMS, Azure portal | Fabric, Data Factory, Databricks, Spark | Power BI, Excel, SQL |
| Our character | Jake (CloudPulse) | FreshMart engineering team | Priya (FreshMart) |
Exam tip: role-matching questions
The exam gives you a task and asks “which role is responsible?” Quick guide:
- “Configure backup and failover” → DBA
- “Build an ETL pipeline” → Data Engineer
- “Create a Power BI dashboard” → Data Analyst
- “Tune a slow database query” → DBA
- “Design the data warehouse schema” → Data Engineer
- “Present sales trends to management” → Data Analyst
Tricky overlap: Both DBAs and data engineers work with databases, but DBAs focus on operational health while engineers focus on data movement and architecture.
Other roles you might encounter
The exam focuses on three roles, but you may see these mentioned:
- Data Scientist: Uses statistics and machine learning to build predictive models. Overlaps with data analysts but focuses on prediction rather than description.
- Data Steward: Manages data governance — ensures data quality, compliance, and proper access controls across the organisation.
- Business Analyst: Similar to data analyst but more focused on business processes and requirements than technical data work.
Flashcards
Knowledge check
FreshMart's data warehouse is running slowly. Queries that used to take 2 seconds now take 30 seconds. Who should investigate and fix the performance issue?
A new data source (IoT sensors from delivery trucks) needs to be connected to Pacific Freight's data warehouse. The data needs to be cleaned, transformed from JSON to tabular format, and loaded every hour. Who should build this?
Next up: The Azure Data Landscape — a map of all the Azure data services you’ll explore in the rest of this course.