Senior Manager, Product Analytics & Data Engineering

Pagero, part of Thomson Reuters, provides a global e-invoicing and business document network that connects more than 14 million businesses across 75+ countries. Pagero is recognized by IDC MarketScape as a Leader in European compliant e-invoicing. As Pagero becomes more integrated with the ONESOURCE ecosystem, the company is expanding its product analytics and data engineering capabilities.

We are hiring a Senior Manager, Product Analytics & Data Engineering to lead the data and analytics strategy for Pagero product and manage a team of analysts and data engineers. This role is responsible for defining analytics priorities, developing team capabilities, and contributing directly to analysis, data pipeline development, and insight delivery.

The role includes evaluating data infrastructure options, testing assumptions, and recommending architecture suited to a regulated transaction environment. It also includes improving product instrumentation across Pagero's global document network to increase visibility into customer experience, customer health, network growth, and product prioritization.

This position is suited for a senior data and analytics leader with experience managing teams, building analytics capabilities, and applying modern AI-assisted tools such as Claude, GitHub Copilot, Cursor, and MCP-based workflows in day-to-day analytics and engineering work.

About the Role:

As Senior Manager, Product Analytics & Data Engineering, you will be responsible for:

• Product Analytics Strategy: Define how data becomes a competitive and operational advantage for Pagero. Set analytical priorities connecting product decisions to network growth, customer retention, integration health, and compliance outcomes, and build the frameworks that make that connection repeatable at scale.
• Product Instrumentation: Own the strategy for how Pagero's product behavior gets measured. Partner with engineering to design and build event-driven data collection across the customer journey: onboarding, transaction success, compliance checkpoints, and trading partner connectivity.
• Data Architecture Evaluation: Lead the evaluation of Pagero's data storage and processing architecture. Engage legal, data platform, and security stakeholders to assess the full range of compliant options, and develop a recommendation covering scalability, cost, and TR integration. Present findings and a clear implementation path to the relevant decision-makers.
• AI-Powered Analytics: Use tools like Claude, GitHub Copilot, Cursor, and MCP-based workflows as a standard part of how analysis gets done and insight gets delivered. Maintain human-in-the-loop review and QA practices to ensure accuracy and appropriate use.
• Team Mandate and Portfolio Focus: In the first 100 days, work with your manager to form a shared view of the team's priorities, end-state, and how to get there with current resources. Identify what the team should own going forward and, where work belongs elsewhere, agree a transition path with the relevant analytics leaders across TR.
• People Leadership: Build, manage, and develop a team of analysts and data engineers with a clear operating model for intake, prioritization, and delivery. Delegate effectively, stay hands-on where it matters, and partner with the Director on hiring and team structure as scope expands.
• Stakeholder Engagement: Serve as the primary product analytics and data partner for Pagero product leadership. Build working relationships with peer analytics leaders across TR, particularly where scope or data infrastructure overlaps. Translate complex technical findings into decision-ready narratives for product, engineering, and senior leadership.

About You:

The ideal candidate for the Senior Manager, Product Analytics & Data Engineering position possesses:

• At least 7 years of experience in product analytics, data engineering, or a related discipline, with at least 3 years leading teams.
• Demonstrated ability to set and execute an analytics and data strategy: defining priorities, building toward them hands-on, and adjusting as context shifts.
• Strong technical foundation spanning data engineering and product analytics: able to evaluate infrastructure options, design measurement frameworks, and partner with engineering to instrument product behavior through event-driven data collection.
• Proficiency in SQL and at least one pipeline language (Python, dbt, or equivalent).
• Familiarity with cloud data platforms (GCP, AWS, Azure, Snowflake, or equivalent) and the architectural trade-offs between them.
• Experience working through data residency, sovereignty, or privacy questions (GDPR, CCPA, or equivalent) in a practical architecture context, including engaging legal and compliance stakeholders to test assumptions rather than inherit them.
• Hands-on experience with AI tooling: LLMs, AI coding assistants (Claude, GitHub Copilot, Cursor, or equivalent), or MCP-based workflows to accelerate analysis, automate workflows, or build data products.
• Experience with product analytics platforms (Pendo, Amplitude, Adobe Analytics, or equivalent), including instrumentation strategy.
• Strong communicator across levels: able to explain infrastructure trade-offs to non-technical executives and give specific technical direction to analysts and engineers.

Nice to have:

• Experience in a post-acquisition or integration environment.
• Experience with e-invoicing, VAT compliance, or B2B transaction platforms

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What’s in it For You?

About Us

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