About the role
Spotter Labs is hiring Accounting Automation Engineers to help automate manual processes across accounting, finance, and related business systems.
This role is for someone who can understand how work is being done today, identify repetitive manual steps, connect data across systems, build automation, and create cleaner workflows that are accurate, repeatable, and scalable.
The initial focus will be Accounting and Finance, but strong performers may also support automation projects in other departments as the company continues to grow.
What You Will Do
Review manual accounting and finance workflows and identify opportunities for automation.
Build repeatable processes across multiple systems, exports, reports, and data sources.
Improve reconciliations, journal-entry preparation, close tracking, reporting, and exception management.
Help connect operational data to accounting and finance processes.
Create templates, scripts, dashboards, workflows, and documentation that reduce manual work.
Work with accounting, finance, operations, and technology teams to understand process gaps and build practical solutions.
Design controls so automation improves accuracy rather than simply speeding up bad processes.
Create exception-based workflows so teams can focus on issues instead of routine data entry.
Document processes clearly so they can be maintained and improved over time.
What We Are Looking For
We are looking for practical automation builders who can work across business systems and messy real-world data.
The ideal candidate has:
Experience automating manual processes using tools such as Excel, Google Sheets, SQL, Python, Power Query, VBA, Google Apps Script, Zapier, Make, Power Automate, APIs, or similar platforms.
Strong ability to work with data exports, reports, spreadsheets, and system-generated files.
Understanding of accounting or finance processes, including reconciliations, journal entries, month-end close, AP, payroll, reporting, or financial analysis.
Ability to map a current process, identify failure points, and build a cleaner workflow.
Strong analytical skills and attention to detail.
Ability to work with non-technical users and translate business problems into automated solutions.
Good documentation habits.
Comfort working in a fast-moving environment where systems and processes are still being built.
Preferred Experience
Experience working with accounting, ERP, banking, payroll, expense management, inventory, reporting, or operational systems.
Experience building dashboards, exception reports, reconciliation tools, or workflow automations.
Experience with multi-system data matching and process improvement.
Experience supporting accounting, finance, operations, logistics, transportation, or other data-heavy business environments.
Accounting, finance, data analytics, systems, or engineering background preferred.
The Type of Person Who Will Succeed
This role is best for someone who likes solving practical business problems.
You should be able to look at a manual process and ask:
Why is this being done manually?
What data is needed?
Where does the data come from?
What can be automated safely?
What should remain subject to review?
How do we prove the output is accurate?
How do we make the process repeatable?
We do not need someone who only writes code in isolation. We need someone who can understand the business process, work with the people doing the work, and build useful automation that holds up in the real world.
Hiring Process
Candidates may be asked to complete a practical work sample involving process mapping, data cleanup, reconciliation logic, automation design, reporting, or workflow improvement.
We are looking for candidates who can understand a problem, organize the data, build a practical solution, document their work, and explain how the process could be improved or automated.
Why This Role Matters
As Spotter Labs grows, the company needs scalable processes instead of more manual work. This role will help build the systems, workflows, and automation needed to support faster reporting, better controls, cleaner data, and more efficient operations.
Originally posted on Himalayas