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Six core data roles, where they sit on the analyze-to-build spectrum, and the actual SQL each one writes day to day. Pick a role to dig in.
The six core roles
Turns business questions into clear answers with SQL and charts.
Comp (relative)
$$$$The most common entry point into data. Analysts answer the questions the business is actually asking: why did signups dip, which segment churns, what should we do next. The work is mostly SQL plus a layer of visualisation and clear communication.
A day in the life
Tools
Related roles
The SQL a Data Analyst writes
A signup-to-purchase conversion funnel.
| step | users |
|---|---|
| visit | 10 |
| signup | 6 |
| purchase | 3 |
Four of the six live in it daily. Build the skill that gets you in the door.
QueryCase Career Hub
Six core data roles, where they sit on the analyze-to-build spectrum, and the actual SQL each one writes day to day.
Turns business questions into clear answers with SQL and charts.
Comp (relative)
$$$$90% SQL
The most common entry point into data. Analysts answer the questions the business is actually asking: why did signups dip, which segment churns, what should we do next. The work is mostly SQL plus a layer of visualisation and clear communication.
A day in the life
Tools
Related roles
BI Analyst · Analytics Engineer · Data Scientist
The SQL a Data Analyst writes
A signup-to-purchase conversion funnel.
SELECT
step,
COUNT(DISTINCT user_id) AS users
FROM events
GROUP BY step
ORDER BY users DESC;| step | users |
|---|---|
| visit | 10 |
| signup | 6 |
| purchase | 3 |
Owns the dashboards and metrics the business steers by.
Comp (relative)
$$$$80% SQL
Business Intelligence analysts own the reporting layer: the dashboards leadership checks every morning and the definitions behind each metric. Less ad-hoc than a Data Analyst, more about consistency, self-serve reporting, and a single source of truth.
A day in the life
Tools
Related roles
Data Analyst · Analytics Engineer
The SQL a BI Analyst writes
Monthly revenue with month-over-month growth.
SELECT
month,
revenue,
ROUND(100.0 * (revenue - LAG(revenue) OVER (ORDER BY month))
/ LAG(revenue) OVER (ORDER BY month), 1) AS mom_growth_pct
FROM monthly_revenue
ORDER BY month;| month | revenue | mom_growth_pct |
|---|---|---|
| 2024-01-01 | 42,000 | NULL |
| 2024-02-01 | 45,500 | 8.3 |
| 2024-03-01 | 43,800 | -3.7 |
| 2024-04-01 | 51,200 | 16.9 |
| 2024-05-01 | 56,900 | 11.1 |
| 2024-06-01 | 54,300 | -4.6 |
Builds the clean, trusted datasets everyone else analyses.
Comp (relative)
$$$$95% SQL
The bridge between raw data and the analysts who use it. Analytics engineers model messy source tables into clean, documented, tested datasets, mostly with SQL and dbt. If a role is almost entirely SQL, it is this one.
A day in the life
Tools
Related roles
Data Analyst · Data Engineer · BI Analyst
The SQL a Analytics Engineer writes
Dedupe raw orders into a revenue-by-customer model.
WITH deduped AS (
SELECT *,
ROW_NUMBER() OVER (PARTITION BY order_id ORDER BY updated_at DESC) AS rn
FROM raw_orders
),
clean_orders AS (
SELECT order_id, customer_id, amount FROM deduped WHERE rn = 1
)
SELECT c.name, COUNT(*) AS orders, SUM(o.amount) AS revenue
FROM clean_orders o
JOIN customers c ON c.customer_id = o.customer_id
GROUP BY c.name
ORDER BY revenue DESC;| name | orders | revenue |
|---|---|---|
| Acme Co | 2 | 390 |
| Initech | 1 | 300 |
| Globex | 2 | 165 |
Uses statistics and ML to predict and explain behaviour.
Comp (relative)
$$$$55% SQL
Data scientists go beyond what happened to what will happen and why. Statistics and machine learning are the core, but it still starts in SQL: most of the job is pulling and shaping data into a clean training set before any modelling begins.
A day in the life
Tools
Related roles
Data Analyst · ML Engineer · Analytics Engineer
The SQL a Data Scientist writes
Build a churn-model training set from user activity.
SELECT
u.user_id,
COUNT(o.order_id) AS order_count,
COALESCE(SUM(o.amount), 0) AS total_spend,
CASE
WHEN MAX(o.order_date) < DATE '2024-05-01' OR MAX(o.order_date) IS NULL
THEN 1 ELSE 0
END AS churned
FROM users u
LEFT JOIN orders o ON o.user_id = u.user_id
GROUP BY u.user_id
ORDER BY total_spend DESC;| user_id | order_count | total_spend | churned |
|---|---|---|---|
| 3 | 2 | 180 | 0 |
| 1 | 2 | 130 | 0 |
| 2 | 1 | 40 | 1 |
| 4 | 1 | 30 | 1 |
| 5 | 0 | 0 | 1 |
Builds the pipelines and warehouses that move all the data.
Comp (relative)
$$$$70% SQL
Data engineers build the plumbing: the pipelines that move and reshape data reliably, and the warehouse that keeps it fast and fresh. Heavier on software engineering and infrastructure, but still deeply SQL-driven once the data lands.
A day in the life
Tools
Related roles
Analytics Engineer · ML Engineer
The SQL a Data Engineer writes
Collapse an append-only event log into current state.
WITH ranked AS (
SELECT *,
ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY loaded_at DESC) AS rn
FROM raw_user_events
)
SELECT user_id, email, status AS current_status
FROM ranked
WHERE rn = 1
ORDER BY user_id;| user_id | current_status | |
|---|---|---|
| 1 | a@example.com | active |
| 2 | b@example.com | active |
| 3 | c@example.com | churned |
Ships machine-learning models into production systems.
Comp (relative)
$$$$35% SQL
ML engineers take a model from a notebook to a live, scalable service: feature pipelines, serving infrastructure, monitoring. The least SQL-heavy of the six, but SQL still shows up whenever features come out of the warehouse.
A day in the life
Tools
Related roles
Data Scientist · Data Engineer
The SQL a ML Engineer writes
Aggregate recent activity into model-serving features.
SELECT
user_id,
COUNT(*) FILTER (WHERE action IN ('click','view')) AS engagement_events,
COALESCE(SUM(value) FILTER (WHERE action = 'purchase'), 0) AS revenue,
MAX(event_date) AS last_seen
FROM activity
WHERE event_date >= DATE '2024-05-01'
GROUP BY user_id
ORDER BY engagement_events DESC;| user_id | engagement_events | revenue | last_seen |
|---|---|---|---|
| 3 | 3 | 60 | 2024-05-25 |
| 1 | 2 | 120 | 2024-05-20 |
| 2 | 2 | 0 | 2024-05-06 |
querycase.com/career-hub/roles · Every one of these roles runs on SQL.