Aggregated from live Data Analyst postings rather than opinion. Every figure below is measured from real adverts and recalculated daily.
A data analyst turns questions people are already arguing about into answers with a number attached — why churn moved last month, whether a change to the signup flow did anything, which of two markets deserves the next hire. In practice that means a lot of SQL against a warehouse someone else built, checking whether the answer survives being looked at a second way, and then presenting it to people who will act on it without reading the query. That last part is not a footnote: an analysis nobody acts on has failed, however correct it was.
Aggregated from the live descriptions of postings whose title names the role. Not a shortlist, and not anybody's opinion of what matters.
Share of Data Analyst postings mentioning the skill — a posting asks for many, so these do not add to 100. Measured across postings whose title is the role.
79 of those 769 remote Data Analyst roles are open to candidates anywhere in the world — the rest are remote within one country only. Most job boards do not separate the two.
The same skill list, split by the seniority of the posting asking for it. Bars run right where senior postings ask more often, left where mid-level postings do.
Percentage-point gap between the senior+ and mid-level shares naming each skill. Senior+ includes principal, staff and executive.
Everyone asks for the top of that first chart, so naming it proves nothing. These sit far enough down to differentiate you, and close enough to the top to be worth the effort.
United States 981 
United Kingdom 490 
Germany 136 
Thailand 121 
Singapore 103 
Netherlands 92 
Malaysia 56 
Canada 53 Where our listings sit, not the world's — the corpus skews to US and English-language boards.
· India
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· Canada
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· Netherlands
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· Netherlands
· Netherlands
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The seniority chart on this page shows something a written list would never surface: the tools most associated with analyst work are not evenly spread across levels. Spreadsheet and dashboard-building skills are asked for noticeably more often in mid-level postings, while SQL, deeper analytics language and mentoring skew toward senior ones. The shift is not that seniors stop using the first set — it is that the postings stop mentioning them, because at that level they are assumed.
Read practically, that gives you two different targets. If you are trying to get the first job, the mid-skewed tools are what the adverts you are answering actually name. If you are trying to move up, the senior-skewed ones are what the next set of adverts will ask for, and the gap between the two lists is a reasonable answer to the question of what to learn next.
"Data analyst" is a title used loosely, which is a genuine limitation here. It covers roles from reporting production in an operations team to something close to data science in a product one, and this page covers all of them. That breadth is why the list mixes warehouse querying with spreadsheet work and why the experience spread is wider than it is for more narrowly defined titles.
The country breakdown is a picture of where the roles we index sit rather than of the world — our corpus is drawn from English-language boards and skews toward the United States. Where a country has a visa sponsorship page of its own, its row links through to the live openings there.
SQL is close to universal in these postings, followed by general analytics language, a visualisation tool, Python, and spreadsheet work. The full ranked list with the share of postings naming each one is at the top of this page, recalculated daily from live adverts.
Most postings cluster at three to five years, but the entry-level share here is substantially larger than for most technical roles on this site, and the six-plus band is small. Those figures are minimums — the lower bound each advert states — and a meaningful share of postings state nothing at all, which is shown rather than hidden.
It is one of the more accessible technical roles by the measure that matters here, which is how many live postings actually accept two years or less. The experience chart above shows that share directly. It is also a common route onward into data engineering or data science, both of which ask for more experience up front.
Less often than SQL, on this evidence — roughly half of these postings name it against four in five for SQL. It is closer to a differentiator than a requirement, which makes it a reasonable thing to learn second rather than first if you are choosing where to spend time.
Some of these roles are remote and a smaller number are open to candidates in any country rather than remote within one — both figures are in the work-policy chart above. Analyst roles sit closer to the business than engineering ones do, which is part of why the hybrid and on-site shares here are larger than you might expect.
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