Senior Data Engineer

ZoomInfo

. Build and own end-to-end pipelines in Python and Airflow ingesting Salesforce, marketing, advertising, conversation intelligence, product usage, billing, and ZoomInfo data into Snowflake .

Posted 11/4/2026full-timeRemote • CanadaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and managing end-to-end data pipelines using Python and Airflow, with a strong focus on data quality, governance, and collaboration across business functions. Proficient in SQL and cloud data warehousing, particularly with Snowflake, while ensuring compliance with data access controls and PII handling.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencySnowflake Data WarehouseAirflow OrchestrationDbt Model Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData Quality AssuranceData TransformationForecasting ModelsCohort AnalysisRoot Cause AnalysisVersion ControlCode ReviewDebugging Complex PipelinesOptimizing Queries

Soft Skills

Strong Communication SkillsAutonomous WorkStakeholder Engagement

Tools & Technologies

AirflowFivetranDatabricksSparkSalesforce

Industry Keywords

Data EngineeringAnalytics EngineeringGTM DataPII HandlingAccess Controls

Tech Stack

Tools & technologies

AirflowBigQueryCloudPythonSnowflakeSparkSQL

About the role

Key responsibilities & impact

Build and own end-to-end pipelines in Python and Airflow ingesting Salesforce, marketing, advertising, 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
Establish certified metrics in the semantic layer with named business-owner approval
Implement tests, monitoring, documentation, and lineage for data quality and reconciliation to Finance
Apply row- and column-level access rules to 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 Data Engineering on definitions and self-serve certified tables
Own post-launch pipelines, participate in the business-hours on-call rotation, investigate root causes, write postmortems, and maintain runbooks
Follow and contribute to engineering standards including version control, code review, CI, and documentation
Help analysts use certified tables and the semantic layer

Requirements

What you’ll need

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 and scope ambiguous requests with stakeholders
Strong communication skills for explaining technical tradeoffs to non-technical partners
Familiarity with PII handling and access controls