Data Operations Lead, B2B

• Support the pre-sales process for large B2B and Lead Gen engagements
• Contribute to Power Digital's marketing measurement programs
• Own the post-signature data onboarding and integration experience for B2B and Lead Gen clients
• Lead structured data intake sessions covering lead definitions, pipeline stage mapping, CRM field configuration, conversion logic, and attribution nuances
• Coordinate CRM, marketing automation, demand generation, call tracking, and form tracking integrations
• Ingest and normalize unstructured lead data from CSV imports, spreadsheets, screenshots, and custom ingress tooling
• Validate integrations and pipeline data before handoff to analytics engineering
• Maintain client integration documentation
• Join sales calls and pitch meetings and conduct pre-signature data audits
• Partner with the Appraisal team to scope data complexity into deal pricing and produce pre-sales data profiles
• Support data readiness for MMM, incrementality, and attribution programs
• Prepare, reconcile, validate, and deliver pipeline-focused measurement data
• Employ AI technologies to enhance and optimize business processes
• Utilize Power Digital's Nova ecosystem as it relates to the department
• Report to the Director of Data Operations & Enablement and collaborate with the Appraisal team, Measurement team, Analytics Engineering, and client account leads

• Proficiency in spoken and written English at an advanced level is required
• 4+ years in data operations, marketing analytics, or marketing technology with direct client or stakeholder-facing responsibilities
• Deep hands-on experience with B2B and Lead Gen data ecosystems, including Salesforce, HubSpot, Marketo, Pardot, LinkedIn Ads, 6sense, and Demandbase
• Proven experience handling unstructured and non-standard lead data ingestion, including CSV imports, manual data entry reconciliation, screenshot-to-data workflows, and custom ingress pipelines
• Solid SQL skills and hands-on Snowflake experience
• Ability to write queries, validate data, and troubleshoot without engineering support for day-to-day tasks
• Comfort in client-facing settings, including speaking to data capabilities in sales conversations and gathering requirements from non-technical marketing stakeholders
• Familiarity with AI-assisted data tooling for unstructured data extraction, schema mapping, or data normalization
• Familiarity with ETL tools such as Fivetran and Funnel and data pipeline concepts

• Equal Opportunity Employer
• Diversity and inclusion valued across race, gender identity, age, disability status, veteran status, sexual orientation, religion, and other identities