London Data & Analytics: Python, SQL, Data Pipelines Lead 695 Roles -- January 2026
BetaLondon's January 2026 data job market featured 695 direct roles from 500 employers, with ML Engineer and Data Engineer as the top specializations and Fintech leading among tracked industries at 23%.
This report analyzes 695 Data & Analytics job postings from 498+ 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
Compensation
Compensation data excluded due to low disclosure rates in markets without pay transparency legislation.
Employers Hiring for Data & Analytics Roles
New This Month
Wise, Rightmove, NBCUniversal
Market interpretation: Among tracked employers, Wise led with 20 open data roles, more than double the next highest employer. Spotify followed at 10 roles. Rightmovecareers (5) and Rightmove Careers (5) are the same employer listed under two different ATS slugs, combining for 10 roles in total. New entrants to the top employer list this month include Wise, Deliveroo, and Rightmovecareers. Note that Robert Half Limited (4 roles) is a staffing agency that was not caught by the agency filter and should be excluded from future counts. The market remained fragmented at 1.39 jobs per employer, with the top 5 holding just 7% and the top 15 holding 13% of all tracked postings.
Industry Distribution
45% of roles with industry data
Biggest Gainer
Fintech
+10pp
Biggest Decline
Professional Services
-9pp
Among the 45% of tracked roles with industry data, Fintech led at 23%, gaining 10 percentage points month-over-month based on a single month's movement. This shift likely reflects London's position as a global fintech hub, with hiring projected to rise 37% YoY in 2026 (Morgan McKinley, January 2026). Professional Services declined 9 percentage points over the same period, which may indicate a seasonal pullback or a reallocation of data hiring toward product-focused companies. Consumer Tech (11%), Financial Services (7%), and E-commerce (7%) formed a stable mid-tier, while AI and ML companies accounted for 7% of tracked industry share.
Role Specialization
Biggest Gainer
Data Architect
+4pp
Biggest Decline
Research Scientist (ML)
-3pp
Among tracked roles, ML Engineer led at 22%, followed by Data Engineer (20%), Data Analyst (18%), and Data Scientist (14%). The top four specializations accounted for 74% of all postings, indicating a concentrated core of demand. Data Architect gained 4 percentage points month-over-month based on a single month's movement, reaching 11% and suggesting growing employer interest in data governance and modeling roles. Research Scientist (ML) declined 3 percentage points to just 1%, which may reflect the niche nature of pure research positions among the tracked employer base. Analytics Engineer (8%) and Product Analytics (5%) represent a growing mid-tier focused on analytics tooling and product-embedded data work.
Seniority Distribution
Junior: 0-2 years | Mid-Level: 3-5 years | Senior: 6-10 years | Staff/Principal: 11+ years (IC track) | Director+: Management track
Biggest Gainer
Senior
+5pp
Biggest Decline
Mid-Level
-11pp
Senior-to-Junior Ratio
7:1
Senior+ roles per Junior role
Entry Accessibility Rate
20%
Junior + Mid-Level roles combined
Among tracked roles, Senior-level positions accounted for 60% of all postings, producing a Senior-to-Junior ratio of 7:1. This ratio is competitive but not exclusionary, with 20% of roles accessible to candidates with fewer than three years of experience (combining Junior at 11% and Mid-Level at 9%). Based on a single month's movement, Senior gained 5 percentage points while Mid-Level declined 11 percentage points compared to December 2025. This shift may indicate that employers are consolidating hiring budgets around experienced practitioners, though one month of data is insufficient to confirm a sustained pattern. Staff/Principal (11%) and Director+ (10%) together accounted for 21%, reflecting continued demand for senior technical leadership among tracked employers.
Company Maturity
42% of roles with company age data
Among the 42% of tracked roles with company age data, Mature companies (over 15 years) and Growth-stage companies (6-15 years) were nearly evenly split at 45% and 43% respectively. Young companies (5 years or fewer) accounted for 11%. This near-parity between mature and growth-stage firms suggests that London's data hiring is not concentrated in either established incumbents or early-stage ventures, but rather spread across a mix of company lifecycles. The relatively small young-company share may reflect the capital constraints faced by early-stage startups in a competitive hiring market.
Ownership Type
43% of roles with ownership data
Among the 43% of tracked roles with ownership data, Private companies accounted for 55%, followed by Public companies at 31% and Subsidiaries at 13%. The private-company majority is consistent with London's large venture-backed fintech and scale-up ecosystem. The 31% public-company share likely reflects large listed employers such as Spotify and ASOS contributing multiple postings. The 13% subsidiary share may indicate that multinational parent companies are running London-based data teams through local entities.
Employer Size Distribution
39% of roles with company size data
Among the 39% of tracked roles with company size data, Enterprise firms (1,000+ employees) led at 45%, followed by Scale-ups (50-1,000) at 36% and Startups (under 50) at 18%. The enterprise-heavy distribution likely reflects that larger organizations post more roles per company and are better represented in ATS tracking. Scale-ups at 36% represent a substantial hiring segment, consistent with London's growth-stage ecosystem. The 18% startup share suggests that smaller companies are active in data hiring but post fewer roles individually.
Working Arrangement
Onsite: office full-time | Hybrid: mix of office and remote | Remote: work from anywhere | Flexible: employee chooses arrangement
97% of roles with known working arrangement
Among 121 ATS-sourced roles with working arrangement data (97% coverage), Hybrid led at 50%, followed by Flexible (24%), Remote (23%), and Onsite (3%). The combined flexibility rate of 97% indicates that nearly all tracked employers offer some form of non-traditional working arrangement. This is consistent with broader UK data showing 85% of companies now offering hybrid options (Advent Communications, 2026). The 23% fully remote share suggests that while remote work remains available, the market has likely settled into a hybrid-first equilibrium. The near-zero onsite share (3%) may further shift as the UK Employment Rights Bill strengthens flexible working rights from April 2026 (UK Parliament, 2026).
Skills Demand
52% of roles with skills data
Skills insight: Among the 52% of tracked roles with skills data (360 roles), Python (34%) and SQL (31%) remained the foundational pair, co-occurring in 21% of postings. The modern data stack was well-represented with dbt (8%), Snowflake (8%), Airflow (6%), and Looker (7%) all appearing in the top 15. Cloud platforms split between AWS (12%) and Azure (7%), with BigQuery (6%) representing GCP presence. AI (10%) and LLMs (6%) emerged as a notable skill cluster, consistent with ML Engineer leading all role specializations at 22%. Data pipelines (12%) and Data modeling (8%) reflect continued demand for core engineering competencies alongside newer tooling.
Market Context
Methodology
This report analyzes direct employer job postings for Data & Analytics roles in London during January 2026.
Data collection:
- 1.Over 600 roles from 500+ employers aggregated from multiple sources
- 2.Recruitment agency postings identified and excluded (7% 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 360 roles with skill data (52% coverage)
- 3.Salary data not included due to low disclosure rates
- 4.Working arrangement based on 121 ATS-sourced roles (Adzuna excluded due to truncated descriptions)
Data coverage:
60%
Seniority coverage
Roles with seniority level classified
97%
Arrangement coverage
Roles with working arrangement known
52%
Skills coverage
Roles with skills extracted from description
54%
Employer metadata
Roles with enriched company data
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