Analytics Engineer III

Sovos Compliance

23h

About The Position

At Sovos, the Analytics Engineer III will be responsible for building the data infrastructure that powers financial intelligence for a global tax compliance leader. This high-impact role involves owning the critical business layer between raw data pipelines and finance teams, ensuring accurate and timely financial numbers. The engineer will partner closely with a Finance Analyst to define and codify core SaaS metrics, validate outputs against NetSuite actuals, and serve as a trusted data voice in the financial close cycle. There is also a defined growth path into AI/MCP engineering as the team plans to activate its AI data layer in Phase 2.

Requirements

• 3–5 years of experience in data analytics or data engineering, with demonstrated ownership of models used in production by finance or operations teams
• Strong SQL skills: CTEs, window functions, complex joins, and the ability to diagnose why a financial model doesn’t match expectations by reading the query
• Production dbt experience – will work directly in the team’s dbt codebase from day one; equivalent frameworks are not sufficient
• Fluency in the revenue data chain (Billing → ARR → Deferred Revenue → Rev Rec → Close Pack) with the ability to debate reconciliation issues directly with a Finance Analyst
• Lived experience working with or embedded in a Finance, FP&A, or RevOps team – understands what close means, why timing matters, and what a board pack is for
• Working knowledge of ASC 606: understands why deferred revenue exists and how recognition timing works well enough to model revenue recognition logic without constant guidance
• Proactive approach to data quality: flags issues before they surface in close, and communicates clearly in both data and finance language
• Demonstrated curiosity and appetite for upskilling – has picked up a new technical skill on the job and shipped something with it; genuine interest in growing into AI/MCP engineering in Phase 2
• Due to client contractual obligations, the successful candidate will be asked to clear a background check and drug test upon hire

Nice To Haves

• Solid data modeling fundamentals: star schema, SCDs, fact vs. dimension tables, and data quality testing patterns
• Python for scripting, data processing, and API integration
• Experience with analytics or BI tools (Tableau, QuickSight, or equivalent) for consuming and validating the reporting layer
• Background in B2B SaaS metrics: ARR, GRR, NRR, pipeline, utilization, and invoice aging
• Strong accountability mindset – checks whether the numbers are right before anyone asks
• Ability to define what “correct” looks like for a given metric and write it down as a testable assertion
• Experience with Model Context Protocol (MCP) or similar AI-to-data integration frameworks
• Cloud basics: Azure or AWS, Git, CI/CD fundamentals
• Domain knowledge in compliance, tax technology, or e-invoicing

Responsibilities

• Own the business-layer dbt models that finance teams query directly, sitting on top of the Senior Data Engineer’s pipeline infrastructure
• Partner with the Finance Analyst to define and codify ARR, NRR, GRR, churn, and deferred revenue metric logic in dbt
• Validate dataset outputs against NetSuite actuals and the Finance Analyst’s source of truth prior to close sign-off
• Serve as an embedded partner in the financial close cycle – proactively flag anomalies and surface exceptions before they become close-day problems
• Act as the primary liaison between data and finance: translate business questions into data models, and translate data outputs back into finance language for FP&A, Accounting, and OTC stakeholders
• Own the data catalogue and documentation for all financial models, maintaining a clear source of truth for what each metric means and how it is calculated
• Extend business-layer metric definitions to cost-side data (OPEX, COGS, commissions, ASC 340-40 capitalized software) as scope expands
• Upskill into MCP/AI engineering in Phase 2 – build MCP server tool schemas, own AI-assisted ARR and revenue forecasting use cases, and manage the prompt library and evaluation framework that determines AI answer quality for finance use cases

Benefits

• Flexible Time-Off
• Comprehensive Health, Dental and Vision benefits
• 401(k) with employee sponsored match
• Bi-Weekly Meeting Free Days
• Mentoring Programs
• Globally recognized Training and Development programs
• Tuition Reimbursement, Time off to Volunteer, Charitable Giving Match, and more!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees