Data analyst salaries are getting destroyed. What happened?
These salary ranges come from Oyster which is an HR/payment platform so these are the averages people are being paid by companies that process their payments through them.
Data Analyst: Mid and Senior level salary varies a lot from 65k to 130k and there's not much difference between them.
For some comparison:
Software Engineer: Salaries range from 90k to 110k for juniors. Mid 120k-140k and Seniors have a pretty wide range of 150k-200k
UX Designer: Senior can range from 80k on the lowest percentile to 165k on the highest, average at 125k so not bad at all actually!
Project Manager: Very good salary range from 120k to 160k.
Customer Success: Salaries range a lot with most principal CSMs at 160k, seniors at 130k. Still though the range in customer success is pretty big.
What happened to this Data Analyst field, automated out? I know salaries used to be way higher and people were talking about this field like the next big thing, but now it's incredibly underpaid and it seems like the job offerings are nowhere to be seen.
Jobadvisor
### Current Salary Landscape for Data Analysts
You're spot on that Data Analyst salaries appear compressed, especially for mid- and senior-level roles, based on the Oyster data you shared (65k–130k USD, with minimal differentiation by experience). This aligns with broader 2025 trends from multiple sources, where the median US salary hovers around $67k–$82k annually, and full ranges span $56k (entry-level) to $119k (experienced, often in high-cost areas or specialized industries). For context:
| Level | Average Salary (USD) | Range (USD) | Key Notes |
|-------|----------------------|-------------|-----------|
| Entry-Level (0–2 years) | $56k–$65k | $41k–$75k | Often requires basic SQL/Excel; heavy competition from bootcamps. |
| Mid-Level (3–5 years) | $76k | $65k–$95k | Focus on dashboards (e.g., Tableau/Power BI); stagnation due to routine tasks. |
| Senior-Level (5+ years) | $100k–$111k | $90k–$130k+ | Broader range in tech/finance; up to $174k remote in niche roles. |
These figures come from aggregated 2025 data across platforms like Payscale, Glassdoor, and ZipRecruiter, reflecting a slight uptick from 2024 but still below inflation-adjusted peaks from 2022 (~$90k median). Oyster's focus on global payroll (including remote/international hires) might skew lower due to cost-of-living adjustments and contractor-heavy data.
In comparison to the roles you mentioned:
- **Software Engineers**: Juniors at 90k–110k make sense—coding is harder to fully automate, and demand remains high for custom dev work.
- **UX Designers**: Seniors averaging 125k (80k–165k) benefit from creative/human-centered skills that AI augments but doesn't replace easily.
- **Project Managers**: 120k–160k reflects leadership/soft skills premiums in volatile markets.
- **Customer Success**: Principals at 160k show value in relationship-building, which scales less via tools.
Data Analysts sit in a "middle ground"—valuable but vulnerable to efficiency tools.
### What Happened? Key Factors Behind the Squeeze
The hype around Data Analytics as "the next big thing" peaked around 2020–2022, fueled by the data explosion post-pandemic. Salaries spiked (e.g., medians hit $85k–$95k), and bootcamps flooded the market with ~500k new entrants annually. But by 2025, several converging forces have "destroyed" that momentum:
1. **Oversaturation and Supply Glut**: The field exploded with accessible education (e.g., Google Data Analytics certs, free Coursera courses), leading to 2–3x more candidates than openings. Entry/mid roles now face fierce competition from laid-off tech workers pivoting in. Remote postings have dropped 20–30% YoY, with Big Tech alums (ex-Meta/Google) dominating.
2. **AI and Automation Eating Routine Work**: Yes, this is a big one—AI tools like ChatGPT, Copilot, and no-code platforms (e.g., Alteryx, Tableau AI) handle 40–60% of basic tasks: data cleaning, simple queries, and dashboard builds. A 2025 IBM report estimates AI cuts analyst costs by 23.5% in data-heavy ops, reducing headcount for juniors/mids. However, it's not full replacement—87% of analysts report AI *enhances* their strategic value, shifting focus to interpretation and business acumen. BLS projects 23% growth for analysts through 2032 (faster than average), but skewed toward seniors with AI fluency.
3. **Economic Headwinds**: Tech layoffs (100k+ in 2024–2025) hit analytics hard, as companies cut "non-core" roles amid recession fears. Broader data science market is down 15% YoY, with AI/ML salaries showing early decline signs too. Job postings are indeed scarcer—LinkedIn reports 15–20% fewer analyst roles vs. 2023 peaks—but demand persists in finance, healthcare, and e-commerce.
Recent X discussions echo this: Posts lament a "poor" market for juniors, with AI blamed for fewer entry gigs, but seniors share wins at $100k+ remote. (From semantic search on "what happened to data analyst salaries" since Jan 2025.)
### Outlook and Advice: Not Dead, But Evolving
The field isn't automated out—BLS forecasts robust growth (23–34% for related roles), driven by data's centrality to decisions. PwC's 2025 AI Jobs Barometer even calls AI a "productivity booster" for automatable jobs like this, potentially lifting top earners. But to hit those higher percentiles (e.g., $150k+ like seniors in your comparisons), differentiate:
- **Upskill Fast**: Master AI integration (e.g., Python for ML, prompt engineering) and soft skills (storytelling via data). Certs in AWS/GCP or advanced SQL pay off.
- **Target Niches**: Finance/healthcare offer 20–30% premiums; remote global roles via Oyster can vary wildly by location.
- **Network/Portfolio**: Build GitHub dashboards; X/LinkedIn shows $80k–$100k gigs going to those with proven impact, not just resumes.
- **Pivot Options**: Blend into Data Science (34% growth, $112k median) or Business Intelligence for less automation risk.
If you're in the field, it's a buyer's remorse moment—but strategic moves can recapture that "next big thing" vibe. What's your experience level or location? I can dig into tailored job leads.