Skill Demand Index
Data Analysis (SQL) — Demand & Depth Analysis
Based on 2 scored job postings out of 4,698 total. Depth levels reflect actual proficiency tiers, not just keyword presence.
0%
Demand Rate
L2
Median Depth
50%
Gap Rate
2
Jobs Analyzed
Minimal
Most employers want Data Analysis (SQL) at introductory awareness.
Overview
What is Data Analysis (SQL)?
Market context for Data Analysis (SQL) in the current job market
Data Analysis (SQL) is required in 0% of scored job postings on ShouldApply, making it a growing skill in the current job market. Employers looking for Data Analysis (SQL) typically want candidates who can demonstrate real proficiency, not just surface awareness.
What the data shows for Data Analysis (SQL):
- •Required in 0% of all scored postings — demand is growing as more employers add it to requirements
- •Employers typically expect L2 depth — foundational knowledge with practical application
- •Most demand comes from Marketing roles — 50% of all Data Analysis (SQL) jobs
What L2 means in practice:
L2 (Basic) means you’ve built small things with Data Analysis (SQL) — personal projects or bootcamp work. Employers accept this for junior roles.
This means employers aren't looking for someone who has used Data Analysis (SQL) once or twice. They want evidence of professional application — shipped work, measurable outcomes, and the ability to operate independently.
Common skill gaps:
The gap rate of 50% means most applicants lack Data Analysis (SQL) at the depth employers need. This is a real opportunity for candidates who invest in building genuine proficiency.
Which roles need Data Analysis (SQL) most:
Marketing positions drive 50% of demand. Product Management also frequently list Data Analysis (SQL) as a requirement. Skills commonly paired with Data Analysis (SQL) include Content Strategy and SEO experience.
Depth Level Distribution
Proficiency Distribution
How candidates match Data Analysis (SQL) requirements across 2 scored evaluations
Average depth: L2.0·Median depth: L2.0
Salary Correlation
Pay Impact
How Data Analysis (SQL) affects compensation based on postings with disclosed salary data
Without Data Analysis (SQL)
$139K
Median $131K
1264 jobs
Skill Demand Insight
“Data Analysis (SQL) appears in 0% of all scored jobs.”
From 2 scored job postings
Skill Pairings
Commonly Paired Skills
Other skills that frequently appear alongside Data Analysis (SQL)
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
Role Breakdown
Top Role Categories
Job categories most likely to require Data Analysis (SQL)
Gap Analysis
Gap Rate Explained
How often Data Analysis (SQL) is identified as a skill gap (L0–L1) in scored applications
Moderate gap rate — many candidates lack this skill
When Data Analysis (SQL) appears in a job's requirements, 50% of scored applicants received an L0 or L1 (missing or minimal).
Frequently Asked Questions
Is Data Analysis (SQL) in demand in 2026?
Yes. Data Analysis (SQL) appears in 0% of scored job postings on ShouldApply, making it a growing skill in the current market. Based on 2 analyzed jobs, demand is steady across multiple role types.
What level of Data Analysis (SQL) do most jobs require?
The median required depth is L2. Many positions accept basic to intermediate proficiency.
Does knowing Data Analysis (SQL) increase salary?
Salary data for Data Analysis (SQL) is still accumulating.
What other skills pair with Data Analysis (SQL)?
The most common pairings are Content Strategy, SEO experience, Enterprise SEO Tools (Conductor, Ahrefs), Understanding of search evolution (AI/LLM), Marketing to Developers/IT. Strengthening these alongside Data Analysis (SQL) improves your fit across more positions.
What roles need Data Analysis (SQL) the most?
Top roles: Marketing, Product Management. Marketing positions have the highest demand at 50% of all Data Analysis (SQL) jobs.
How do I improve my Data Analysis (SQL) level?
L1→L2: online courses and personal projects. L2→L3: daily professional use and shipped work. L3→L4: mentoring others and optimizing processes. L4→L5: architecture decisions, open source contributions, or published work.
See how you stack up against Data Analysis (SQL) job requirements
ShouldApply scores your profile against each skill at the depth level jobs actually need.
Analyze my Data Analysis (SQL) gaps →See how your depth compares to what employers actually require
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