Senior Data Engineer

ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen fast. The Senior Data Engineer is a core builder of the single source of truth that ZoomInfo's Corporate Strategy and GTM Strategy teams use to plan and track the business: pipeline created, bookings, conversion, renewals, market size, and results against plan. The same certified tables and metric definitions will later feed the Company Brain, the company-wide knowledge layer that employees and AI agents query. What you will do: • Build and own end-to-end pipelines in Python and Airflow that ingest Salesforce, marketing, ad platform, conversation intelligence, product usage, billing, and ZoomInfo data into Snowflake. • Bring plan, quota, headcount, and cost data from Finance, RevOps, and HR systems into the warehouse so Strategy teams can compare results to plan and calculate • Establish certified metrics in the semantic layer, each approved by a named business owner, so dashboards, spreadsheets, and AI agents reuse one definition. • Implement tests, monitoring, documentation, and lineage for uniqueness, completeness, freshness, and reconciliation to Finance, and alert before a stakeholder finds the problem. • Apply row- and column-level access rules so only cleared people can see sensitive fields such as compensation and quota. • Run forecasts, territory and capacity models, cohort and retention studies, and impact readouts • Partner with Corporate Strategy, GTM Strategy, Business Partners, Finance, RevOps, and central Data Engineering to agree on definitions before building, and turn recurring requests into self-serve certified tables. • Own pipelines after launch: share the business-hours on-call rotation, find root causes, write short postmortems, and keep runbooks current. • Follow and contribute to team engineering standards, including version control, code review, CI, and documentation, and help analysts use certified tables and the semantic layer. What you bring: • 5+ years in data or analytics engineering, with demonstrated ownership of production pipelines in a cloud warehouse. • Strong SQL and Python; comfortable writing production-grade code, debugging complex pipelines, and optimizing queries • Hands-on experience with a cloud data warehouse (Snowflake strongly preferred; BigQuery or equivalent acceptable). • Solid dbt experience — has built and maintained models in a production dbt project • Experience with orchestration tools — Airflow and Fivetran required; Dagster or equivalent a plus • Experience with Databricks and Spark for custom modeling and transformation workloads • Experience with GTM data in Salesforce or another CRM, including opportunity history, bookings, and renewals • Ability to work autonomously — can take an ambiguous ask, scope it with a stakeholder, and ship a solution with minimal oversight • Strong communication skills — can explain technical tradeoffs to non-technical partners and adapt style to different audiences • Security-first mindset; familiar with PII handling and access controls Preferred qualifications • Hands-on experience working with Finance, Marketing, Sales data to support data driven decision • Built a semantic layer (dbt Semantic Layer, Cube, LookML, or similar) that more than one tool reads from • Prepared data for AI use: documented fields, lineage, access controls, and agent tool access such as MCP servers • Built time-series forecasts of pipeline, bookings, or renewals • Built territory, capacity, or market-sizing