Data Analyst, Product

Kraken Digital Asset Exchange

Operate as a full-stack data analyst within the Pro team, owning your domain completely while collaborating closely with colleagues across the pod.; Own the design and evolution of dashboards, north star metrics and analytical frameworks t…

Posted 7/24/2026Verified active Jul 25, 2026, 12:36 AMfull-timeRemote • London • 🇬🇧 United KingdomWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrated expertise in data analytics and engineering, with a strong focus on building and maintaining scalable data infrastructure and production pipelines. Proven ability to lead experimentation and A/B testing frameworks, delivering actionable insights and recommendations that influence product strategy and drive business outcomes.

Highest-signal resume keywords

7+ Years of Experience in Data Analytics or Analytics EngineeringHands-on Experience with Advanced Trading ProductsStrong Familiarity with dbt and AirflowFull Mastery of SQL and Strong Python ProficiencyExperience Leading Cross-Functional Data Initiatives

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalyticsAnalytics EngineeringSQLPythonA/B Testing

Soft Skills

Strong CommunicationData StorytellingCollaborationInfluencing Technical DirectionSimplifying Complex Ideas

Tools & Technologies

DbtAirflowAI ToolingLLM-Augmented PipelinesGenAI-Assisted Analytics

Certifications & Qualifications

Degree in Software EngineeringDegree in EconomicsDegree in Hard Science

Industry Keywords

FintechPaymentsFinancial MarketCryptoData Quality

Tech Stack

Tools & technologies

AirflowPythonSql

About the role

Key responsibilities & impact

Operate as a full-stack data analyst within the Pro team, owning your domain completely while collaborating closely with colleagues across the pod.
Own the design and evolution of dashboards, north star metrics and analytical frameworks that drive decisions at the highest level of the business.
Build and maintain data infrastructure at scale, from scalable dbt models and production pipelines to full-funnel reporting that powers cross-functional teams.
Lead experimentation across the Product domain by designing and owning A/B testing frameworks, applying causal inference techniques and turning results into clear, confident recommendations that influence product strategy.
Influence technical direction across the data team, contributing to how we build, what we prioritise and how we raise the bar on data quality and engineering standards.
Embed AI tooling into your workflow in ways that have tangible business impact, including LLM-augmented pipelines and GenAI-assisted analytics workflows.
Deliver insights through clear, data-driven storytelling to technical and non-technical audiences, including senior leadership.

Requirements

What you’ll need

7+ years of experience in data analytics or analytics engineering, ideally within fintech, payments, financial market or crypto where data quality and scale are non-negotiable.
You have hands-on experience with advanced trading products and solutions in equities, crypto, or other assets. You either have a professional background working within financial markets or on a trading desk, or you are a professional trader.
Hands-on experience building and owning production data pipelines, with strong familiarity with dbt and Airflow or equivalent orchestration tools.
Full mastery of SQL including complex joins, CTEs and analytical functions, alongside strong Python proficiency for pipeline development and analysis.
Hands-on experience designing and running A/B tests and experimentation frameworks, with the ability to apply causal inference techniques and translate results into clear growth recommendations.
Demonstrated experience leading cross-functional data initiatives from design to delivery, with measurable business outcomes you can point to.
Strong communicator who can simplify complex data ideas for both technical and non-technical audiences.
A degree in a field emphasising analytical rigour such as software engineering, economics or a hard science.
Based in Canada, the US, the UK or the EU and fluent in English.
Experience with LLM-augmented analytics pipelines or AI-assisted workflows in a production environment