Senior Finance Systems Analyst

Description:

We are hiring a Senior Finance Systems Analyst to own this layer end-to-end. This is a senior individual contributor role with real scope and visibility, you will define how Finance systems connect, build the automation and reconciliation controls the business depends on, and shape how Finance operates as we grow into new markets and regulatory environments.

The immediate priority is leading the completion of the Kyriba implementation: bringing PSP and bank integrations live, building the Tableau reporting layer on top of it, and establishing the operational controls that make Finance reporting reliable and scalable. From there, the role owns the quality and reliability of all Finance automation across the stack.

Responsibilities:

Complete outstanding PSP and banking integrations and remaining bank feeds
Own the Kyriba data push to the Data Warehouse; close the existing pipeline gap
Maintain exchange rate feed integrity and ensure reloads cascade correctly to Kyriba and all downstream Finance systems
Serve as the technical escalation point for Kyriba, and own the vendor relationship and roadmap alignment
Build and own the Tableau reporting layer for Kyriba data, replacing the current FM dependency
Define and own data contracts and mapping logic across NetSuite, Kyriba, Abacum and the Data Warehouse
Coordinate with the Data Engineering team to centralize Finance signals and prevent stale or duplicate data
Own the communication loop between Finance Analytics and DE so that recalculations propagate correctly, eliminating the balance mismatch and data lag issues Finance currently experiences
Align the Abacum actuals feed from NetSuite for accurate FP&A reporting
Implement daily automated tests: count/total reconciliation per pipeline, anomaly detection with Finance notification alerts, and a regression test suite before every BI release
Build and maintain external fee reconciliation: maintain the fee agreement register (bank fees, LP fees, PSP fees) and automate matching of internal GL records against agreements and external statements
Publish an Automation Health Dashboard (uptime, last run timestamp, exception count) visible to Finance leadership
Define and own SLAs for all automated Finance processes; report performance against them
Run the Finance BI backlog: triage requests, manage UAT and regression cycles, and move Finance from informal Slack requests to a structured, predictable delivery process
Own triage and small hotfixes when automations fail; coordinate resolution with Dev/DE teams
Run root-cause analysis after every incident and update controls to prevent recurrence
Maintain runbooks, a control matrix, and a data dictionary for all Finance BI objects

Requirements:

Hands-on experience with a Treasury Management System: Kyriba strongly preferred, equivalent TMS experience (GTreasury, Quantum, Integrity) considered
Strong NetSuite experience: configuration, scripting, workflows, saved searches, and ideally GL/multi-entity setup
SQL proficiency: you are comfortable writing queries to investigate data issues, validate reconciliations, and build monitoring routines
Demonstrated experience owning finance system integrations end-to-end: mapping, validation, alerting, and incident resolution
Solid understanding of core Finance processes - GL, treasury, FP&A, bank reconciliation. You can translate Finance requirements into technical solutions without a hand-holding intermediary
Track record of building in ambiguous environments: you don’t need a perfect spec to make progress
Experience with Abacum or comparable FP&A planning tools
Tableau or Power BI: ability to build and maintain Finance dashboards, not just consume them
Familiarity with Airflow or similar orchestration tools for monitoring pipeline health
Experience working in a regulated financial services environment (banking, fintech, brokerage)
Exposure to data warehouse architecture and working relationships with Data Engineering teams
Familiarity with AI-assisted tools (e.g. for SQL generation, data analysis, or workflow automation) and a mindset of leveraging AI to improve efficiency and system reliability