Job Specifications
About the Company
This company operates in the digital asset and financial technology space, building infrastructure and products that support a modern, internet-native financial system. The environment is data-rich, technically demanding, and built around turning complex product and platform data into clear commercial insight.
The team sits close to product, engineering, and analytics, with a strong focus on reliable data foundations, scalable modeling, and practical tools that help the business make better decisions.
The Role
This is a Senior Analytics Engineering seat for someone who can move comfortably across data engineering, analytics, and business problem-solving. You’ll own data models, pipelines, and internal tooling in a defined domain, while working closely with technical and non-technical partners to turn messy inputs into decision-grade data products.
What You Will Do
Build and maintain core data models that give teams a dependable foundation for reporting, analysis, and experimentation
Partner with product, engineering, and analytics stakeholders to translate business questions into scalable datasets, dashboards, and workflows
Develop and improve data pipelines from source through transformation to delivery, while identifying and closing gaps in upstream data quality
Create reusable tools and abstractions such as Python packages, and internal data applications that make downstream work faster and more consistent
Step into new business areas, learn the underlying systems quickly, and use data to solve practical product and commercial problems
What You Bring
Strong experience designing modular, reusable data models, including dimensional modeling approaches such as star or snowflake schemas
Advanced SQL skills and solid Python capability, including scripting, automation, and object-oriented development
Hands-on experience building and optimizing ETL or ELT workflows using tools such as dbt, Airflow, or similar platforms
Comfort working across modern analytics environments, including BI tools, version control, CI/CD workflows, and cloud data platforms such as Snowflake or Databricks
A track record of working cross-functionally, explaining technical work in business terms, and applying sound statistical thinking to real-world product or operational questions
Why This Role
This is a strong fit for someone who wants broad ownership, close partnership with product and engineering, and the chance to shape how data is structured and used across a complex platform. You’ll be working on high-value problems where better pipelines, better models, and better tooling directly improve how the business operates.