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Added 24 mins ago
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Toronto, ON
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ZoomInfo Technologies LLC

Senior Data Engineer

Toronto, ON, Canada

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Job details

Posting language: English
Posted: Nov 4, 2026

Original job description

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 models
Used LLMs to classify or extract fields from unstructured text such as call transcripts
Data observability tools such as Monte Carlo or Datadog, and AWS or GCP with Terraform
Familiarity with ZoomInfo data or similar company and contact data

#LI-

About us:

ZoomInfo (NASDAQ: GTM), the all-in-one AI GTM platform, enables sales, marketing, and customer success teams to execute their go-to-market strategy with confidence. Powered by the industry's most comprehensive B2B data, including more than 100 million companies, 500 million contacts, and billions of signals, ZoomInfo delivers the intelligence, automation, and integrations that modern revenue teams need to identify, engage, and convert their best buyers.

ZoomInfo is committed to protecting your privacy when you apply for jobs with us. Please review our Job Applicant Privacy Notice for more details on how we handle your personal information.

ZoomInfo may use a software-based assessment as part of the recruitment process. More information about this tool, including the results of the most recent bias audit, is available here.

ZoomInfo is proud to be an equal opportunity employer, hiring based on qualifications, merit, and business needs, and does not discriminate based on protected status. We welcome all applicants and are committed to providing equal employment opportunities regardless of sex, race, age, color, national origin, sexual orientation, gender identity, marital status, disability status, religion, protected military or veteran status, medical condition, or any other characteristic protected by applicable law. We also consider qualified candidates with criminal histories in accordance with legal requirements.

For Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. ZoomInfo does not administer lie detector tests to applicants in any location.

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More about this job

Responsibilities

Build and maintain production data pipelines that integrate business, sales, marketing, finance, HR, and product data into Snowflake, and establish certified metrics and secure, well-documented data models. Partner with strategy and business teams on forecasts and analytical models, support self-service data use, and own pipeline reliability, monitoring, incident response, and engineering standards.

Requirements

Requires 5+ years of data or analytics engineering experience, strong SQL and Python skills, production dbt experience, and hands-on experience with a cloud data warehouse; Snowflake is preferred. Airflow and Fivetran experience are required, with experience in CRM/GTM data, Databricks and Spark, security controls, stakeholder communication, and autonomous delivery also sought.

Skills

SQL
Python
Snowflake
dbt
Airflow
Fivetran
Databricks
Spark
Data Pipeline Engineering
Data Modeling
Semantic Layer Development
Salesforce
Data Orchestration
Data Quality Monitoring
Access Controls
Forecasting

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Snowflake
Airflow
Fivetran
dbt
Databricks
Spark
Salesforce
BigQuery
Dagster
Data Engineering
Analytics Engineering
Data Pipelines
Cloud Data Warehouse
Semantic Layer
Data Lineage
Data Observability
Data Quality
Access Controls
PII
GTM Data
Finance Data
Marketing Data
Forecasting
Territory Modeling
Capacity Modeling
Cohort Analysis
LLMs
Terraform

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