Kraken-posted 2 months ago
Mid Level

As a Data Analyst, Growth at Kraken, you will play a crucial role in elevating decision-making by uncovering emerging trends and root causes, and by developing tools to drive insight and actions that give full visibility into business performance and growth. You will own end-to-end data management, from building and maintaining datasets and pipelines to designing dashboards and insights for the Growth team. Additionally, you will work on experimentation infrastructure, launching an A/B testing system together with your team and contributing to other experimental projects to ensure the data team is constantly evolving and growing.

  • Act as a trusted business advisor who influences decision-making for the growth team and deeply understands the business.
  • Own the design of dashboards, metrics, and reports, turning data into actionable insights for the growth team, cross functional partners, and the leadership team.
  • Dive into large, complex datasets/logs to turn findings into scalable data models necessary to facilitate reporting, analytics and ML models.
  • Lead cross-functional projects with analysts, scientists, engineers, and product teams to build data pipelines using Airflow, Python, and modern ETL frameworks.
  • Develop and automate reporting of key performance indicators of various Kraken’s products at scale.
  • Develop high-quality code for pipelines and dashboards, incorporating software engineering best practices.
  • Deliver insights that shape growth direction through clear, data-driven storytelling.
  • At least 3 years of industry experience in data analysis and data management roles within the financial services industry, with exposure to trading product solutions.
  • Hands-on experience using dbt (data build tool) to model and organize marketing, product, or performance data for reporting and decision-making.
  • Experience supporting marketing growth teams, with exposure to business KPIs such as NTUs (New Trading Users) and other performance marketing metrics.
  • Proficiency in SQL and familiarity with Python libraries such as pandas, matplotlib, and plotly.
  • Experience setting up and managing data pipelines, with a strong understanding of data workflow orchestration.
  • Capable of creating intuitive dashboards and visualizations to communicate complex insights clearly.
  • Strong communicator who can simplify complex data ideas for both technical and non-technical audiences.
  • A degree in a field emphasizing analytical rigor, such as software engineering, economics, or a hard science.
  • Fluency in English.
  • Deep interest in improving user experiences through better product analytics and experimentation.
  • Passion for continuous learning and approaching problems with a beginner’s mindset.
  • Solid understanding of the cryptocurrency space and how financial markets function.
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