Compensation & Analytics Partner

Fivetran | Anywhere in the World

완전히 원격 풀타임 데이터 과학 및 분석
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설명

Headquarters: CRI - Remote

From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven.

About the Role

We are looking for a Staff Compensation & Data Analyst (IC4) to serve as the subject matter expert at the intersection of quantitative analysis, compensation strategy, HR technology, and AI-assisted analytics. In this role, you will lead the architecture, modeling, and execution of our global compensation programs while leveraging modern AI platforms and scalable data pipelines.

As a Staff level technical authority, you will drive business-critical compensation initiatives—from merit cycles and pay modeling to global equity strategy. You will partner with Finance, Legal, and Stock Administration on equity program design and governance, collaborate closely with Systems Engineering on Workday Compensation design and testing, utilize Carta for equity analytics, and leverage enterprise Generative AI platforms (Claude, ChatGPT) to accelerate data synthesis, narrative reporting, and predictive analytics.

This is a full-time remote position based in Costa Rica. 

What You’ll Do 

Strategic Compensation Analytics & AI-Assisted Modeling

• Architect Compensation Models: Build and maintain complex models for salary band creation, market pricing, geographic differentials, and merit/promotion budget allocation using quantitative techniques and advanced spreadsheet/coding frameworks.

• AI-Augmented Data Analytics: Leverage enterprise AI platforms (e.g., Claude, ChatGPT) to conduct exploratory analysis on large workforce datasets, synthesize compensation survey benchmarks, evaluate market trends, and automate repetitive data transformation workflows.

• Executive & Incentive Pay: Partner with leadership to model executive total compensation, short-term incentive (STI) performance metrics, and long-term incentive (LTI) grant strategies, utilizing AI tools to generate executive-level narrative summaries and scenario analyses.

Strategic Equity Strategy & Global Program Design

• Global Equity Design & Modeling: Partner with stakeholders to design and model strategic global equity frameworks,including refresh plan design, grant guidelines, vesting schedules, and budget allocations.

• Stock Administration Partnership: Work in tandem with Stock Administration to establish seamless workflows for equity grant approvals, board consent materials, vest schedules, and data reconciliation between equity systems and core HRIS.

• Equity Systems & Analytics (Carta): Utilize Carta and internal analytics tools to model wealth creation scenarios and executive equity usage to inform strategic compensation decisions.

Workday Partnership & Data Infrastructure

• Workday Compensation Design & Rollouts: Partner closely with Systems Engineering to co-design, test, administer, and execute Workday Compensation and Advanced Compensation workflows, eligibility rules, and global merit cycle rollouts.

• Data Integration & Pipeline Development: Collaborate with Systems Engineering to ensure seamless data flows between Workday, payroll systems, external survey management platforms, and analytical databases.

• Custom Reporting & BI: Design, build, and audit complex Workday custom reports, matrix reports, and calculated fields to deliver real-time total rewards insights to business leaders. Use BigQuery for querying, analyzing, and transforming large-scale datasets.

Enablement, Change Management & Training

• Program Enablement & Change Management: Apply structured change management principles to drive adoption of total rewards initiatives, merit updates, pay transparency changes, and compensation program rollouts.

• Communications & Collateral Creation: Develop comprehensive, clear, and engaging communications materials—including manager guidebooks, FAQ docs, slide decks, and video walk-throughs—tailored to various audiences.

• Stakeholder Training: Design and facilitate targeted training sessions for managers, Talent Acquisition (TA), HR Business Partners (HRBPs), and employees to build compensation and equity literacy.

Skills We’re Looking for

Experience

• 6+ years of progressive experience in compensation analysis, equity strategy, or People Analytics, with demonstrable mastery at a senior/principal individual contributor level.

• Proven track record of designing and modeling global compensation and equity programs in partnership with Finance in a fast-paced or scaling technology environment.

• Demonstrated experience with change management and driving enablement programs, including producing training collateral and leading educational workshops for cross-functional teams.

Technical & System Proficiency

• Workday Compensation: Hands-on experience working directly with Workday Core Compensation and Advanced Compensation modules is required.

• Carta & Equity Management: Hands-on experience or strong familiarity with Carta for cap table analytics, grant administration alignment, and LTI modeling is strongly preferred.

• AI Platforms & Prompt Engineering: Experience applying Large Language Model (LLM) tools such as Claude, ChatGPT, or Microsoft Copilot to data analysis, code generation (SQL/Python/Excel formulas), or report generation is strongly preferred.

• Advanced Analytics & BI: Advanced proficiency in Excel, Google Suite (VBA/macros, dynamic arrays, complex formulas) is required. Experience with BI and BigQuery tools for data modeling is a strong plus.

Core Competencies

• Cross-Functional & Executive Alignment: Exceptional ability to build strong cross-functional partnerships across Finance, Legal, Stock Admin, and Systems Engineering to deliver complex total rewards solutions.

• Quantitativ

작업 세부 정보

경험: 0 년

게시됨: 1 hour, 33 minutes 날짜

보기: 4

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