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London · London, England, United Kingdom
Actively hiring, first seen by us todayLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: EngineeringFrom the employer’s posting
2-5 years of experience in analytics, data, or operations (internships count)
Good communication skills - able to explain insights clearly and visually
Experience with BI or visualization tools (Metabase, Looker, etc.)
Strong SQL skills for querying and exploring datasets
Familiarity with dbt for building and maintaining data models, writing tests, and managing transformations
Experience contributing to a shared analytics codebase or modern data stack (e.g., Snowflake/BigQuery + dbt + Git workflow)
From the employer’s posting.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 0
Early. Similar jobs usually come down between day 6 and day 47.
From 1,417 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Strong SQL skills for querying and exploring datasets - Comfortable reading code and writing basic Python scripts for data manipulation, automation, and analysis - Experience contributing to a shared analytics codebase or modern data stack (e.g., Snowflake/BigQuery + dbt + Git workflow)
- 2-5 years of experience in analytics, data, or operations (internships count) - Strong SQL skills for querying and exploring datasets - Comfortable reading code and writing basic Python scripts for data manipulation, automation, and analysis
- Comfortable reading code and writing basic Python scripts for data manipulation, automation, and analysis - Experience contributing to a shared analytics codebase or modern data stack (e.g., Snowflake/BigQuery + dbt + Git workflow) - Analytical curiosity and a structured approach to problem solving
- Experience with BI or visualization tools (Metabase, Looker, etc.) - Familiarity with dbt for building and maintaining data models, writing tests, and managing transformations - Exposure to fraud, financial, or product analytics (any domain welcome)
- STEM degree preferred (e.g., Mathematics, Computer Science, Engineering, Physics, Economics, or related fields) - Experience with BI or visualization tools (Metabase, Looker, etc.) - Familiarity with dbt for building and maintaining data models, writing tests, and managing transformations
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Are you curious about how things work and motivated by uncovering insights hidden in data?
As a Platform Analytics Engineer at ARQ, you’ll help us understand our business, customers, and operations through rigorous analysis and thoughtful storytelling. You’ll explore data, detect patterns, and build the foundations for decisions that shape the future of our products and company.
This is a role for someone who wants to grow - learning how data drives product, financial, and strategic decisions in a fast-paced fintech environment.
Explore and Analyze Data: Investigate user behavior, performance trends, and key metrics to uncover what’s driving changes.
Identify Anomalies and Opportunities: Spot unusual patterns or spikes and help the team understand their root causes.
Reporting & Automation: Build and maintain dashboards and automated reports that make data accessible and reliable.
Decision Support: Translate analytical findings into clear recommendations for product and operational improvements.
Metric Design: Help define and refine the KPIs that matter most for our business and customer experience.
Documentation: Keep analyses, methodologies, and assumptions well-documented and reproducible.
Modeling & Experimentation: Contribute to basic modeling tasks and structured experiments under guidance from senior analysts or data scientists.
Continuous Learning: Expand your analytical toolkit and develop product sense through real-world problem solving and mentorship.
2-5 years of experience in analytics, data, or operations (internships count)
Strong SQL skills for querying and exploring datasets
Comfortable reading code and writing basic Python scripts for data manipulation, automation, and analysis
Experience contributing to a shared analytics codebase or modern data stack (e.g., Snowflake/BigQuery + dbt + Git workflow)
Analytical curiosity and a structured approach to problem solving
Good communication skills - able to explain insights clearly and visually
Initiative to automate repetitive tasks and improve reporting workflows
Interest in fintech, data-driven decision-making, and machine learning concepts
Ambitious, high-potential mindset with evidence of strong achievement, fast progression, or outstanding academic/professional performance.
Nice to have
STEM degree preferred (e.g., Mathematics, Computer Science, Engineering, Physics, Economics, or related fields)
Experience with BI or visualization tools (Metabase, Looker, etc.)
Familiarity with dbt for building and maintaining data models, writing tests, and managing transformations
Exposure to fraud, financial, or product analytics (any domain welcome)
Spanish/Portuguese proficiency for internal and external communications.
Competitive salary and benefits
Stock options, so you own part of what you build
Discretionary performance bonus
The latest tools and technology
A world-class team that will challenge and grow your skills
The opportunity to help build the best fintech app in Latin America
Office Policy: 3-4 days a week in-office
Selected passages from the saved posting. Check the full description for conditions and exceptions.
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London, England, United Kingdom
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.