Manager, Finance Analytics Engineering & Automation

Overview

Manager of Finance Analytics Engineering & Automation who turns Finance requirements into trusted analytical data products, reusable consumption layers, automated workflows, controls, and integrations, working closely with FP&A, Finance Data & Analytics, Data Engineering, and business partners.

What you'll do

• Own Finance analytics engineering and automation across Snowflake, SQL, workflow automation, controls, integrations, and downstream Finance consumption.
• Translate Finance requirements and approved business definitions into scalable technical solutions, working with Finance Data & Analytics on product priorities and with Data Engineering on enterprise pipelines and platform standards.
• Build and maintain Finance-ready consumption views, analytical models, reconciliations, and reusable datasets that make governed enterprise data easier for FP&A and Finance users to consume without unnecessary duplication.
• Perform hands-on SQL analysis, lineage tracing, impact assessment, and root-cause investigation across Finance data flows, especially when definitions, sources, joins, or upstream systems change.
• Establish and automate technical controls for critical Finance processes, including reconciliations, data-quality checks, regression tests, monitoring, release validation, and recovery procedures.
• Lead Finance automation and workflow engineering, setting standards for maintainability, production support, documentation, ownership, and reusable patterns across tools such as Alteryx, Python, APIs, or comparable platforms.
• Serve as a primary Finance technical partner to Data Engineering, helping separate Finance-owned analytical logic from deeper platform engineering while ensuring clean handoffs and clear ownership.
• Support the technical architecture and productionization of AI-assisted Finance workflows and analytical agents, with emphasis on governed sources, deterministic execution where needed, traceability, testing, and safe failure.
• Manage and develop Finance automation engineering capacity, including coaching team members, strengthening backup coverage, and building durable technical capability rather than key-person dependency.
• Partner across FP&A, Accounting, RevOps, Product, IT, and other teams to deliver cross-system solutions that are practical for Finance users and sustainable in production.

What you'll need

• 6+ years of experience in FP&A, finance analytics, analytics engineering, financial data, automation, or a related technical Finance role.
• Strong Finance or FP&A domain knowledge and the ability to understand how business definitions, planning processes, reporting, and controls translate into technical requirements.
• Strong hands-on SQL skills and experience working in Snowflake or a comparable cloud data platform, including data modeling, lineage analysis, validation, troubleshooting, and building reporting- or consumption-ready datasets.
• Demonstrated ability to move from an ambiguous Finance question to a trustworthy data answer by interrogating source data, challenging assumptions, and validating results.
• Experience building or supporting analytical consumption layers, semantic or reporting-ready datasets, reusable views, or similar Finance-facing data products.
• Experience building automated analytical workflows using tools such as Alteryx, Python, dbt, APIs, or comparable platforms.
• Working knowledge of production controls, testing, monitoring, documentation, change management, and root-cause analysis.
• Prior people management or strong technical-lead experience, with the ability to coach hands-on practitioners while also setting technical direction.

Nice to have

• Experience in a SaaS or subscription business, including exposure to ARR, bookings, renewals, revenue, or other recurring Finance metrics.
• Experience partnering with centralized Data Engineering teams while owning Finance-specific analytics, consumption, or automation layers.
• Familiarity with ERP, CRM, planning, HRIS, and reporting platforms such as NetSuite, Salesforce, Anaplan, Workday, or Tableau.
• Experience with data governance, semantic layers, metadata, lineage, or certification practices.
• Experience evaluating or productionizing AI-assisted analytics, LLM, agent, or MCP-style workflows where accuracy, traceability, and controls matter.

Details

• Remote-friendly position in the United States.
• Salary range in the United States: $139,475 - $151,970, plus possible bonus eligibility.
• Export controls: any offer is contingent on the applicant's capacity to serve in compliance with U.S. export controls.