Denver Data & Analytics: Python, SQL, AWS Lead 1,099 Roles -- December 2025

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Denver'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 Hiring Managers

1.0Differentiate on Flexibility Terms With 67% of roles already remote, simply offering remote work is table stakes. Differentiate through other factors: async-first culture, equipment stipends, co-working allowances, or quarterly in-person gatherings that create community without mandating relocation.

1.1Reconsider Junior Hiring Strategy The 11:1 senior-to-junior ratio means most companies are competing for the same senior talent. Consider structured junior programs - with 21% entry accessibility, candidates exist but few companies invest in developing them. This can build loyalty and reduce long-term recruiting costs.

1.2Align Compensation with Market Reality Among tracked roles, 25% disclose salary ranges. Senior roles cluster around $177,500 median while Staff positions reach $235,000. Posting below market will likely filter out informed applicants - transparency cuts both ways.

1.3Compete Beyond the Big Names Oracle, Pinterest, and Deloitte collectively hold only 9% of tracked postings, so no single employer leads the market. Smaller companies can compete effectively by emphasizing impact, equity potential, and career growth that larger firms cannot match.

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

Employers Hiring for Data & Analytics Roles

Large employers with proprietary career sites (Amazon, Google, Meta, Microsoft) may be underrepresented, as our sources primarily capture roles posted through standard direct employer platforms and job aggregators. We are actively expanding our integrations.

Low

High

Market interpretation: Among tracked employers, Oracle leads with 4% share, followed by Pinterest (3%) and Deloitte (2%). Notable is the mix of enterprise tech (Oracle, Amazon), consumer platforms (Pinterest, Reddit, Instacart), professional services (Deloitte), defense (Lockheed Martin), and financial services (Capital One, Coinbase), demonstrating Denver's cross-industry data hiring.

Industry Distribution

68% of roles with industry data

Low

High

Denver's industry mix balances consulting (Professional Services, 14%) with product companies (Consumer Tech, 14%), reflecting the region's dual identity as both a services hub and emerging tech center. The strong Data Infrastructure presence (12%) indicates substantial investment in the platforms and tools that power modern data operations. Healthcare (9%) shows Denver's growing life sciences sector, while Fintech and E-commerce (7% each) demonstrate diversification beyond traditional tech verticals.

Role Specialization

Low

High

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.

Seniority Distribution

Junior: 0-2 years | Mid-Level: 3-5 years | Senior: 6-10 years | Staff/Principal: 11+ years (IC track) | Director+: Management track

Low

High

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.

Company Maturity

66% of roles with company age data

49%Growth Stage

Growth (6-15 yrs)49%

Mature (>15 yrs)44%

Young (<=5 yrs)8%

Growth-stage companies (6-15 years) lead hiring at 49%, representing firms that have achieved product-market fit and are scaling their data capabilities. Mature enterprises (44%) provide stability and structured career paths, while the modest young company segment (8%) reflects reduced venture funding for early-stage firms. This distribution offers job seekers a balanced choice between growth potential and stability.

Ownership Type

66% of roles with ownership data

51%Private

Private51%

Public41%

Subsidiary6%

Acquired2%

The market splits between private companies (51%) and public firms (41%), offering distinct compensation structures. Private company roles often include equity that could appreciate meaningfully, while public company positions provide liquid stock compensation and typically more predictable total compensation. The low acquired segment (2%) suggests recent M&A activity has not materially disrupted hiring patterns.

Employer Size Distribution

66% of roles with company size data

53%Enterprise

Enterprise (1,000+)53%

Scale-up (50-1,000)34%

Startup (<50)13%

Enterprises lead hiring at 53%, reflecting Denver's attraction of established tech companies and traditional industry leaders investing in data capabilities. Scale-ups (34%) represent high-growth firms with substantial resources but often faster career progression. The startup segment (13%) offers higher risk-reward profiles with greater ownership potential but less job security. This enterprise-heavy composition explains the relatively strong salary figures and abundance of senior roles.

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

67%Remote

Remote67%

Flexible14%

Hybrid12%

Onsite7%

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.

Skills Demand

71% of roles with skills data

Low

High

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.

Market Context

1.Remote Work Hub Evolution Denver emerged as a premier remote work destination during the pandemic, attracting tech workers from higher-cost coastal cities. The 67% remote rate reflects both local companies embracing distributed models and national firms hiring remotely into the Colorado talent pool, creating an unusually flexible market compared to other major metros.

2.AI/ML Production Maturity The leading share of ML Engineers (26%) over traditional Data Scientists (16%) suggests that Denver employers have moved beyond experimental AI phases into production deployment. Companies are now hiring for systems that need to scale and maintain reliability, not just prototype models - a sign of market maturity.

3.Enterprise Data Modernization With 53% of roles at enterprises and strong demand for modern data stack tools (Airflow, Snowflake, dbt), Denver reflects broad enterprise adoption of cloud-native data infrastructure. Traditional companies are investing heavily in updating legacy systems, creating opportunities for engineers who can bridge old and new architectures.

4.Colorado Pay Transparency Impact Colorado's pay transparency law contributes to salary disclosure, though only 25% of tracked roles include employer-disclosed salary ranges after removing predicted and estimated figures. This narrower but more reliable compensation data still benefits job seekers and likely creates some pressure for employers to remain competitive, contributing to Denver's relatively strong compensation despite lower cost of living than coastal hubs.

5.Growth-Stage Company Concentration Nearly half of hiring (49%) comes from companies 6-15 years old, representing the sweet spot of startup maturity. These growth-stage firms have proven business models and funding but still offer meaningful equity and career acceleration opportunities not available at mature enterprises, making Denver attractive for ambitious professionals.

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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