B
Evidence Grade B
Graded
accuracy verified by the review judge
Safe to Cite
Current
44%
44% -- share of time building and maintaining pipelines for data engineers (2026)
Data engineers spend roughly 44% of their time building and maintaining pipelines rather than doing net-new analytical work.
Attribution:
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Lighthouse Research Team
Last verified:
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Source verified
Evidence graded
Value
44%
Unit
Percentage
Data Vintage
2026
Entity
Sample Size
300
Geography
North America
Evidence Quality
B
Strong, reliable evidence
Sourced from a well-regarded research firm or industry leader with transparent methodology and a reasonably large sample.
Single source - not yet corroborated
Score breakdown
Extraction
75
Source Trust
60
Citation Chain
60
Independence
30
Methodology
45
Freshness
95
Source
Fivetran / Wakefield Research
Primary
Tier B
https://www.datamagnet.co/post/build-vs-buy-gtm-enrichment-layer/ ↗
Source Article
Build vs. Buy: Should You Build Your Own Enrichment Layer?
Disclosure: This article is published by Datamagnet. Vendor claims are self-reported unless otherwise noted.
Build vs. Buy: When Should GTM Engineers Build Their Own Enrichment Layer?
Most GTM engineers should buy the data layer and build the workflow on top of it — but that answer flips fast once y…
Original Research
Fivetran / Wakefield Research
· Original study ↗
Methodology
Fivetran and Wakefield Research survey of 300 data and analytics leaders
Methodology documented
Segmentation
IndustryTechnology
Company SizeEnterprise
RegionNorth America
Cite this stat
Plain Text
data engineers: 44% share of time building and maintaining pipelines. Source: Fivetran / Wakefield Research (2026). Via Lighthouse Intelligence -- https://lighthousedata.io/data/fivetran-pipeline-time-2026
HTML Embed
<blockquote cite="https://lighthousedata.io/data/fivetran-pipeline-time-2026" style="border-left:3px solid #2563eb;padding:12px 16px;margin:16px 0;font-family:system-ui,sans-serif;background:#f0f4ff;"><strong>44%</strong> -- share of time building and maintaining pipelines for data engineers<br><small>Source: Fivetran / Wakefield Research (2026) · <a href="https://lighthousedata.io/data/fivetran-pipeline-time-2026" target="_blank" rel="noopener">Lighthouse Intelligence</a></small></blockquote>
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