Denver Data & Analytics: Python, SQL, AWS Lead 1,099 Roles -- December 2025
BetaDenver's data market offers strong remote flexibility with 67% of roles fully remote and a more accessible entry point than coastal hubs, though competition remains intense with an 11:1 senior-to-junior ratio across 1,099 positions from 485 employers.
This report analyzes 1,099 Data & Analytics job postings from 485+ companies tracked via direct employer career pages and job board aggregators. Our coverage skews toward tech-forward and scaling companies; large enterprises using enterprise hiring platforms may be underrepresented. Coverage varies by section and is noted throughout.
Key Takeaways for Job Seekers
Skills Demand
71% of roles with skills data
Skills insight: Python (46%) and SQL (39%) remain the foundational skills, appearing together in 28% of roles - the highest skill pair frequency. The modern data stack trinity of Airflow (11%), Snowflake (10%), and dbt (10%) shows strong adoption, with these tools frequently paired with core SQL skills. AWS leads cloud platforms at 15%, with GCP and Azure tied at 8%, reflecting multi-cloud reality. The PyTorch (8%) and LLMs (7%) presence points to growing AI/ML infrastructure investment, while Looker (7%) indicates continued business intelligence requirements.
Seniority Distribution
Junior: 0-2 years | Mid-Level: 3-5 years | Senior: 6-10 years | Staff/Principal: 11+ years (IC track) | Director+: Management track
Senior-to-Junior Ratio
11:1
Senior+ roles per Junior role
Entry Accessibility Rate
21%
Junior + Mid-Level roles combined
Senior individual contributors lead at 51%, reflecting the market's preference for experienced practitioners who can contribute immediately. Staff/Principal roles (20%) indicate substantial need for technical leadership, while Director+ positions (8%) show demand for organizational leaders. The 7% junior segment, while small, represents nearly 80 entry-level opportunities - meaningful for a mid-sized market. The 21% entry accessibility rate (Junior + Mid-Level) makes Denver notably more accessible than coastal markets. Note: The 11:1 ratio reflects all senior-level roles (Senior + Staff/Principal + Director+) divided by Junior positions.
Working Arrangement
Onsite: office full-time | Hybrid: mix of office and remote | Remote: work from anywhere | Flexible: employee chooses arrangement
50% of roles with known working arrangement
Denver's 67% fully remote rate stands out as notably high, likely driven by the region's emergence as a distributed work hub during the pandemic. Combined with flexible (14%) and hybrid (12%) options, 93% of roles offer some degree of location flexibility. Only 7% require full-time onsite presence. This distribution makes Denver one of the most accommodating major data markets for professionals prioritizing geographic freedom.
Role Specialization
ML Engineers hold the largest share at 26%, suggesting that Denver employers are moving beyond experimental AI into production systems requiring strong engineering. Data Engineers (21%) support this infrastructure buildout. The combined Data Scientist and Analyst share (32%) shows continued need for insights-focused roles, while Data Architects (7%) indicate enterprise-scale system design requirements. The emerging Analytics Engineer role (4%) reflects growing adoption of modern analytics engineering practices.
IC vs Management Track
The 90% IC focus reflects data and analytics work's fundamentally technical nature - most value creation happens through hands-on work with data, models, and systems. The 10% management segment provides career progression opportunities for those seeking people leadership, though the predominant path remains technical advancement through Staff and Principal levels.
Compensation
25% of roles with disclosed salary ranges
Overall Distribution
25th Percentile
$160K
Median
$185K
75th Percentile
$228K
IQR (Spread)
$68K
Advertised Salary by Seniority
Advertised Salary by Role
Market Context
Methodology
This report analyzes direct employer job postings for Data & Analytics roles in Denver during December 2025.
Data collection:
- 1.Over 1,000 roles from 485+ employers aggregated from multiple sources
- 2.Recruitment agency postings identified and excluded (3% of raw data)
- 3.Jobs deduplicated across sources to avoid double-counting
Classification:
- 1.Roles classified using an LLM-powered taxonomy
- 2.Subfamily, seniority, skills, and working arrangement extracted
- 3.Employer metadata enriched from company databases where available
Limitations:
- 1.Not a complete census of the market - some roles may not be captured
- 2.Skills analysis based on 775 roles with skill data (71% coverage)
- 3.Salary data limited to 25% of roles with employer-disclosed ranges; predicted and estimated salaries excluded for reliability
- 4.Working arrangement specified in 50% of postings
Data coverage:
85%
Seniority coverage
Roles with seniority level classified
50%
Arrangement coverage
Roles with working arrangement known
70%
Skills coverage
Roles with skills extracted from description
68%
Employer metadata
Roles with enriched company data
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