GTM Data Operations Manager

At Algolia, we’re proud to be a pioneer and market leader in AI Search, empowering 18,000+ businesses to deliver blazing-fast, predictive search and browse experiences at internet scale. Every week, we power over 30 billion search requests — four times more than Microsoft Bing, Yahoo, Baidu, Yandex, and Duck Duck Go  combined. In 2021, we raised $150 million in Series D funding, quadrupling our valuation to $2.25 billion.

This strong foundation enables us to keep investing in our market-leading platform and serving incredible customers like Under Armour, Pet Smart, Stripe, Gymshark, and Walgreens.

Algolia is seeking a detail-oriented and proactive GTM Data Operations Manager to join our Revenue Operations team to ensure our customer and prospect data is trusted, governed, and operationally sound across the entire GTM ecosystem. The GTM Data Operations Manager owns the operational health, governance, and integrity of customer and prospect data across the company's go-to-market systems. The role is responsible for ensuring Leads, Contacts, Accounts, and related GTM data are accurate, enriched, synchronized, and governed to enable effective execution across Marketing, Sales, Customer Success, and Analytics.

Data Stewardship, Governance & Quality Act as the operational steward for customer and prospect data (Leads, Contacts, and Accounts) across the GTM ecosystem, ensuring data is accurate, complete, consistent, and trusted.

Own operational governance for customer and prospect data across Salesforce, Marketo, Demandbase and related integrated GTM systems, including data quality standards, telemetry requirements, validation rules, field governance, and operational policies.

Execute recurring hygiene programs including deduplication, standardization, enrichment validation, and lifecycle management; partner with system owners to resolve data integrity issues.

Partner with business stakeholders to evaluate requests for new fields, objects, and data standards while maintaining integrity and consistency across the ecosystem.

Identify data quality risks, drive remediation efforts, and support the evolution of GTM data models as business needs change.

Data Enrichment & Identity Management:
Administer enrichment workflows across GTM platforms. Monitor enrichment success rates and troubleshoot failures. Maintain enrichment mappings and integrations. Partner with GTM Technology on vendor implementations and improvements.

Data Operations:
Monitor critical integrations between Salesforce, Marketo, Demandbase and other GTM systems. Investigate synchronization failures and scope / support implementation to minimize future failures. Ensure customer and prospect data flows reliably across systems. Support operational readiness for new fields, objects and integrations as well as deprecation of those no longer needed.

Operational Excellence:
Support complex audience segmentation requests requiring deep knowledge of GTM data structures. Provide operational data support for strategic GTM initiatives as required. Ensure GTM data is structured and governed to support scalable reporting, automation, and AI-powered workflows. Document data processes and governance standards. Develop dashboards to monitor data quality health. Identify automation opportunities that improve operational efficiency. Support audit and compliance requests.

• 3+ years of experience in Revenue Operations, Marketing Operations, Sales Operations, CRM Administration, Data Operations, or a related GTM operations function.
• Strong working knowledge of Salesforce and CRM data management principles, including Leads, Contacts, Accounts, and related data structures.
• Experience working with marketing automation platforms (e.g., Marketo) and GTM data platforms and enrichment technologies.
• Familiarity with SQL and data warehouse concepts (e.g., Hex, Databricks, Thought Spot, etc) is a plus.
• Understanding of CRM architecture, lead lifecycle management, data enrichment, and system integrations across the GTM technology stack.
• Experience maintaining data quality through governance, validation rules, deduplication, standardization, and…