Vacancy details
This is a private vacancy. Company details stay confidential until InVault confirms a serious candidate fit.
- Status
- Active
- Date posted
- 2026-11-15
- Open until
- 2027-02-13
- Employment type
- Full-time
- Source-listed languages
- Not specified
- Language requirement
- No mandatory language inferred
- Work arrangement
- Remote
- Physical workplaces
- Not specified
- Applicant eligibility
- United States
Overview
Develop trusted financial analytics datasets and automated reconciliation workflows for digital-asset operations. Work with finance and data engineering teams to build tested pipelines, reporting and a finance data lake, investigate accounting discrepancies and replace recurring manual close work with reliable automation.
Requirements
- At least seven years of experience in data analytics and data management within financial services or another regulated industry, working directly with finance teams.
- Strong production SQL and Python engineering, including debugging and maintaining code.
- Hands-on experience building pipelines and data models with dbt, Spark, Airflow or comparable tools.
- Experience with Git, code reviews, testing and clear technical documentation.
- Direct experience handling accounting and finance data such as subledgers, reconciliations, cost basis or month-end closing.
- Ability to own end-to-end production data pipelines, monitor quality and resolve financial data discrepancies.
- Excellent communication with accounting and engineering stakeholders.
- Prior cryptocurrency transaction data or large-scale distributed-finance-data processing is advantageous, not mandatory.
Responsibilities
- Build tested data pipelines and analytical models for financial reporting.
- Automate finance data preparation, reconciliation, exception handling and recurring close activities.
- Investigate accounting data discrepancies with finance and engineering teams.
- Develop financial dashboards and support trusted finance data-lake reporting.
- Maintain pipeline controls, monitoring, data definitions and operational documentation.
- Evaluate reliable automation improvements, including AI-assisted workflows.
Conditions
- Full-time, fully remote position within the United States.
