Data Operations Lead, B2B

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Data Operations Lead, B2B based in Brazil. This is an exciting opportunity for a data operations specialist to lead B2B and lead generation data integration, onboarding, and measurement initiatives in a technology-driven digital growth environment. You will bridge the gap between marketing, sales, analytics, and engineering, ensuring complex data sources are transformed into reliable, actionable business intelligence. From CRM integrations and marketing automation to unstructured lead data and revenue attribution, you will own critical data workflows throughout the client lifecycle. You will also support pre-sales engagements, assess technical requirements, and help shape realistic onboarding plans for prospective clients. By combining strong analytical expertise with AI-assisted data tools, you will improve data quality, streamline operations, and strengthen marketing measurement. This remote opportunity is ideal for a proactive professional who enjoys solving complex data challenges and communicating technical concepts to diverse stakeholders.

Own B2B and Lead Generation Data Onboarding: Manage the end-to-end data onboarding process for new clients, from initial scoping and requirements gathering through integration, validation, and measurement readiness. Lead Data Discovery and Requirements Gathering: Conduct structured intake sessions to document lead definitions, pipeline stages, CRM field configurations, conversion logic, and attribution requirements. Coordinate Data Integrations: Establish and validate data connections across CRM platforms such as Salesforce and HubSpot, marketing automation tools such as Marketo and Pardot, demand generation platforms such as LinkedIn Ads, 6sense, and Demandbase, and call tracking and form capture tools such as CallRail and Unbounce. Manage Unstructured Data Ingestion: Transform non-standard data sources, including CSV files, manual spreadsheets, screenshot-based reports, and custom data feeds, into structured, usable datasets through normalization, schema mapping, and AI-assisted extraction where appropriate. Validate Data Quality and Readiness: Confirm that integrations are operational, data is accurately captured, and required information is available before transferring validated datasets to analytics engineering for further modeling. Maintain Integration Documentation: Create and maintain clear, up-to-date client-specific documentation covering data sources, field mappings, integration configurations, known limitations, and attribution considerations. Support Pre-Sales Engagements: Participate in sales calls and presentations for prospective B2B and lead generation clients, communicating technical capabilities, integration approaches, and onboarding processes with confidence. Conduct Pre-Sales Data Assessments: Evaluate prospective clients' CRM configurations, data quality, attribution methodologies, and integration complexity. Identify technical risks, custom requirements, and potential implementation challenges before contracts are finalized. Contribute to Project Scoping and Pricing: Collaborate with internal appraisal and commercial teams to translate data complexity, fragmented CRM environments, and custom ingestion requirements into realistic effort estimates and project expectations. Enable Marketing Measurement Programs: Support measurement initiatives, including marketing mix modeling (MMM), incrementality analysis, and attribution programs for B2B and lead generation clients with long sales cycles and offline conversions. Prepare and Reconcile Measurement Data: Ensure lead volumes, qualified pipeline data, and closed revenue records are reconciled, validated, and delivered according to modeling specifications. Leverage AI and Data Technologies: Apply AI-assisted extraction, schema mapping, normalization, and automation tools to improve operational efficiency, data quality, and scalability. Use the organization's internal technology ecosystem to support departmental workflows. Monitor Performance and Delivery Standards: Track onboarding timelines, client data coverage, and ingestion success rates, working toward defined targets for reliable data availability and timely delivery. Requirements: Professional Experience: At least 4 years of experience in data operations, marketing analytics, or marketing technology, with direct client-facing or stakeholder-facing responsibilities. B2B and Lead Generation Expertise: Strong hands-on knowledge of B2B marketing data ecosystems, including CRM platforms such as Salesforce and HubSpot, marketing automation platforms such as Marketo and Pardot, and demand generation or account-based marketing tools such as LinkedIn Ads, 6sense, and Demandbase. Unstructured Data Processing: Proven experience ingesting, reconciling, and normalizing non-standard lead data, including CSV imports, manual spreadsheet submissions, screenshot-based reporting, and custom data ingestion pipelines. SQL and Data Validation: Solid SQL skills and practical Snowflake experience, with the ability to write queries, validate datasets, investigate discrepancies, and troubleshoot routine data issues independently without relying on engineering support. Data Integration and ETL: Familiarity with data pipeline concepts and ETL or integration tools such as Fivetran, Funnel, or equivalent platforms. Marketing Attribution and Measurement: Understanding of lead lifecycle management, pipeline attribution, conversion tracking, and the relationship between marketing activities, qualified opportunities, and revenue outcomes. Experience supporting measurement programs involving long sales cycles or offline conversions is valuable. AI-Assisted Data Operations: Familiarity with AI-enabled tools for data extraction, schema mapping, normalization, and processing of unstructured information. Client and Stakeholder Communication: Confidence participating in sales discussions, explaining technical capabilities, and gathering requirements from non-technical marketing stakeholders. You should be able to translate complex data challenges into clear recommendations. Analytical and Problem-Solving Skills: Strong attention to detail, a structured approach to data quality, and the ability to identify integration risks, diagnose data issues, and develop practical solutions. Organization and Ownership: Ability to manage multiple client onboarding projects, maintain accurate documentation, prioritize competing requirements, and deliver against defined timelines and service-level expectations. Cross-Functional Collaboration: Comfortable working with sales, analytics, measurement, account management, and engineering teams to ensure smooth implementation and reliable downstream reporting. Advanced English Proficiency: Strong spoken and written English skills are required for effective collaboration with international clients and distributed teams. Performance Orientation: Ability to work toward measurable operational targets, including onboarding completion within three weeks, timely processing of non-standard data sources, and comprehensive coverage of active B2B and lead generation clients. Benefits: Remote Work: Work remotely from Brazil as part of a distributed, technology-driven team. Collaborative Environment: Partner with specialists across data operations, marketing measurement, analytics engineering, and client strategy. AI-Enabled Workflows: Access AI-powered tools and proprietary technology designed to improve data analysis, operational efficiency, and decision-making. Professional Development: Opportunities to deepen expertise in B2B data operations, marketing technology, attribution, data integration, and AI-assisted workflows. Career Growth: Develop your expertise at the intersection of data engineering, marketing analytics, client delivery, and commercial strategy. Meaningful Client Impact: Help organizations improve the reliability of their marketing data, strengthen measurement capabilities, and connect marketing investment to business outcomes. Inclusive Workplace: Join a people-focused environment that values diverse backgrounds, perspectives, collaboration, accountability, and continuous learning.