Senior Analytics Engineer - Finance

Sobre a oportunidade

Join a globally distributed data engineering team working at the intersection of financial data, accounting, and advanced analytics.

Local

São Paulo - SP

Remoto

Responsabilidades

Develop financial data products: Design, build, and maintain reliable data pipelines, transformation models, and analytics solutions that support financial reporting, accounting operations, and business decision-making.

Automate financial workflows: Partner with Finance teams to identify operational bottlenecks and implement automated processes for data preparation, reconciliations, reporting, and follow-ups, incorporating appropriate controls, monitoring, and exception handling.

Improve reporting and visualization: Create intuitive dashboards and data visualizations that help stakeholders monitor financial performance, investigate discrepancies, and make informed decisions.

Investigate and resolve data discrepancies: Collaborate with Finance, Product, and Engineering teams to diagnose reconciliation breaks, identify root causes, validate financial outputs, and communicate progress toward resolution.

Build scalable data pipelines: Collect, transform, and curate data from internal platforms and external systems, ensuring data accuracy, reliability, scalability, and accessibility.

Strengthen financial data infrastructure: Contribute to the development and implementation of a trusted finance data lake, establishing clear data definitions, ownership, quality controls, and validation processes.

Enhance data availability: Improve the timeliness of financial information and enable near-real-time insights where they deliver meaningful business value.

Leverage AI and emerging technologies: Evaluate new tools, prototype AI-assisted automation solutions, and integrate suitable technologies into production workflows to reduce repetitive work and accelerate development.

Support financial close activities: Improve recurring accounting and month-end close processes through sustainable automation, reliable data models, and transparent reconciliation workflows.

Ensure engineering excellence: Apply strong software engineering practices, including testing, documentation, version control, code reviews, and ongoing monitoring, to maintain production-quality data solutions.

Collaborate across technical and financial teams: Translate business needs into technical requirements, communicate complex findings clearly, align priorities with stakeholders, and encourage adoption of new data products.

Requisitos

At least 7 years of experience in data analytics and data management within financial services or another regulated industry, including direct collaboration with Finance teams.

Strong proficiency in SQL and Python, including the ability to develop, debug, test, and maintain production-grade code.

Hands-on experience building and operating data pipelines and transformation models using dbt, Spark, Airflow, or comparable technologies.

Solid experience with Git, merge requests, code reviews, automated testing, and technical documentation.

Direct experience working with financial or accounting data, including reconciliations, subledgers, cost basis, or month-end close processes.

Ability to investigate financial discrepancies, validate outputs with accounting stakeholders, identify root causes, and implement durable solutions.

A proven track record of owning data pipelines throughout their lifecycle, making sound architectural decisions, and improving system reliability as business requirements evolve.

Experience supporting recurring financial close activities and identifying opportunities to replace manual processes with scalable, maintainable automation.

Strong judgment, attention to detail, and the ability to navigate ambiguous problems while remaining accountable for production outcomes.

Excellent communication skills, with the ability to explain technical issues and their financial implications to both technical and non-technical stakeholders.

Ability to prioritize complex work independently, collaborate across multidisciplinary teams, and adapt solutions to changing systems and business needs.

Diferenciais

Remote work: Work remotely from Brazil as part of an internationally distributed team.

Technical ownership: Lead important financial data initiatives and influence the architecture and reliability of production data systems.

Cross-functional collaboration: Work closely with Finance, Accounting, Data Engineering, Product, and Platform teams.

Professional development: Expand your expertise in financial analytics, data engineering, accounting automation, and emerging AI-assisted technologies.

Meaningful impact: Improve financial reporting, data quality, operational efficiency, and decision-making across a global digital asset business.

Innovation-driven environment: Explore modern data technologies and automation approaches while solving complex financial data challenges.

Inclusive workplace: Join an organization that values diverse backgrounds, perspectives, and professional capabilities.