Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system.
Before you apply, we encourage you to explore our culture page to understand what drives us and how we work.
Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.
At Kraken, the data team is the infrastructure layer beneath every product decision. We're not looking for someone to report on what happened. We're looking for someone who builds the systems that make it possible to know at all and then uses them to shape what happens next.
We're looking for a Senior Data Analyst, Product to join our team remotely. This is a staff-level individual contributor role where you will own the Product domain end to end. You won't just be answering questions. You'll be deciding which questions are worth asking, building the infrastructure to answer them at scale, and influencing the technical direction of the team along the way. Experimentation is core to how we work. We run rigorous A/B tests, apply causal inference at scale and treat experimentation as a first-class discipline, not an afterthought.
You'll own production-grade pipelines, dbt models, dashboards and metric frameworks. You'll define north star metrics, drive experimentation infrastructure and translate results into clear business recommendations. You'll also play an active role in shaping how AI tooling is embedded into how we work, from LLM-augmented pipelines to GenAI-assisted workflows that have real, measurable impact on the business.
At this level, we expect more and we expect it faster. You'll operate with a high degree of autonomy, move quickly without sacrificing quality, and set a bar that raises the team around you.
Operate as a full-stack data analyst within the Product 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 and growth 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.
10+ years of experience in data analytics or analytics engineering, ideally within fintech, payments, crypto or a high-scale marketplace where data quality and scale are non-negotiable.
Proven track record of building and owning data infrastructure at scale, not just using it. You've built the pipelines, defined the models and taken ownership of what happens when things break.
Deep expertise with dbt is a must. You've used it in production, you know its limits and you've built models that others depend on.
Strong experience managing ELT/ETL pipelines end to end, with hands-on familiarity with Airflow or equivalent orchestration tools.
Full mastery of SQL and strong Python proficiency for pipeline development, analysis and production-grade code.
Deep hands-on experience designing, running and owning experimentation programmes including A/B testing frameworks and causal inference at scale. You've built the infrastructure, not just used it, and you can translate results into clear business decisions.
Experience deploying AI tools including LLM-augmented pipelines or GenAI-assisted workflows with demonstrable business impact.
A track record of influencing technical direction and data strategy, not just executing within it.
Strong communicator who can simplify complex data ideas for both technical and non-technical audiences, including senior leadership.
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.
Nice to haves
Solid understanding of the cryptocurrency space and how financial markets function.
Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.
Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.
We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto.
We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision.
As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws.
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