Manager, Finance Analytics Engineering & Automation

Overview

This hands-on management role sits at the intersection of Finance, analytics engineering, and automation. The position will translate Finance requirements into trusted analytical data products, reusable consumption layers, automated workflows, controls, and integrations. You will partner closely with FP&A, Finance Data & Analytics, Data Engineering, and business stakeholders to make governed enterprise data easier for Finance to use while improving reliability, scalability, and decision support.

This role is not a central data engineering position and not a traditional Finance systems administration role. Enterprise Data Engineering continues to own deeper platform and production-pipeline engineering. Instead, the focus is closer to Finance: understanding business questions, tracing source data and lineage, shaping Finance-ready analytical layers, and building repeatable solutions that are controlled, supportable, and useful for decision-making.

Responsibilities

• 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, partnering 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 to reduce unnecessary duplication and improve usability for FP&A and Finance users.
• Conduct 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 to separate Finance-owned analytical logic from deeper platform engineering while ensuring clean handoffs and clear ownership.
• Support technical architecture and productionization of AI-assisted Finance workflows and analytical agents, emphasizing 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.

Requirements

• 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 translate business definitions, planning processes, reporting, and controls 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. Deep Alteryx expertise is not required.
• 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.

Preferred Qualifications

• 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.

Compensation & Benefits

• Final compensation will be determined by relevant work experience, education, certifications, skills, and geographic location.
• Salary range (United States): $139,475 - $151,970.
• Additional compensation may include a bonus.
• Benefits may include medical, retirement, financial, wellness, time off, employee discounts, and others.

Location

Remote-friendly.

For roles in San Francisco and Los Angeles: In accordance with local fair chance requirements, qualified applicants with arrest and conviction records will be considered.

This position involves access to software/technology subject to U.S. export controls. Any job offer is contingent upon the applicant’s capacity to serve in compliance with U.S. export controls.