Finance Data Engineer: Trusted Analytics & Automation

Finom; United States; Remote; USD 71,000 - 945,000; Full time

Job summary

Finom is seeking a Senior Analytics Engineer for Finance to partner with treasury, reconciliation and accounting teams. You’ll design and scale the finance data model, build trusted data products, and own the data lineage, tests and documentation to support close, reporting and investor dashboards.

You’ll work with a modern stack, choose tools, and drive data quality and automation, turning business needs into scalable data solutions that reduce manual work and accelerate decision making.

Qualifications

• Experience working in finance data or FP&A data partnerships.
• Strong SQL skills and ability to build dimensional models and semantic layers.
• Proven track record delivering data products used by multiple teams.

Responsibilities

• Partner with Treasury, Reconciliation and Accounting teams on processes and data needs.
• Build treasury data: positions, cash flows and liquidity as trusted data products.
• Scale reconciliation so matching and breaks are handled systematically.
• Support Accounting with data, checks and integrations for close and daily work.
• Assist corporate finance data partner on investor reporting with a unified model.
• Design and evolve the Finance data model with tests, lineage and documentation.
• Set data standards and quality checks; build integrations with Finance systems.
• Introduce automation and agents in Finance workflows to reduce manual work.
• Connect data work to business cost and value and drive improvements.

Skills

SQL

Data modelling

ETL

Data products

Consultant mindset

Tools

Databricks

Unity Catalog

Data warehouse

Job description

Finom is seeking a Senior Analytics Engineer for Finance to partner with treasury, reconciliation and accounting teams. You’ll design and scale the finance data model, build trusted data products, and own the data lineage, tests and documentation to support close, reporting and investor dashboards.

You’ll work with a modern stack, choose tools, and drive data quality and automation, turning business needs into scalable data solutions that reduce manual work and accelerate decision making.