Senior Analytics Engineer - Finance Data & Automation

Kraken International; United States; Remote; USD 130,000 - 210,000; Full time

Job summary

Kraken is seeking a Senior Analytics Engineer to join the Finance Data Eng & Analytics team within the Data Platform. You will build trusted financial data products, using automation and AI to reduce manual work and improve the close process.

Working at the intersection of data engineering and accounting, you’ll turn complex financial data into reliable pipelines, models and automated reconciliations while ensuring outputs are tested and traceable.

Qualifications

• 7+ years of data analytics experience in financial services or regulated industry.
• Strong SQL and Python skills with production code.
• Experience building and operating pipelines using dbt, Spark, or Airflow.
• Direct experience with finance data such as reconciliations, subledgers, or month-end close.
• Proven track record owning pipelines end-to-end and improving reliability.

Responsibilities

• Collaborate with Data Engineers, Finance and Platform Accounting to improve reporting and decision-making.
• Translate business needs into practical data and automation solutions.
• Build and maintain automated workflows for data preparation, reconciliations, reporting and follow-ups.
• Build intuitive dashboards and visualizations for stakeholders to understand performance and investigate issues.
• Resolve data issues and reconciliation breaks with Finance, Product and Engineering.
• Develop scalable pipelines to collect, transform and curate data from internal and external sources.

Skills

SQL

Python

Automation

Data analysis

Communication

Tools

Git

dbt

Spark

Airflow

Job description

Kraken is seeking a Senior Analytics Engineer to join the Finance Data Eng & Analytics team within the Data Platform. You will build trusted financial data products, using automation and AI to reduce manual work and improve the close process.

Working at the intersection of data engineering and accounting, you’ll turn complex financial data into reliable pipelines, models and automated reconciliations while ensuring outputs are tested and traceable.