# Senior Analytics Engineer

**Company**: ZoomInfo
**Location**: Toronto, ON
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/zoominfo/jobs/8879302002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_58779f68-67c

## Description

ZoomInfo is seeking an experienced Senior Analytics Engineer to join the Enterprise Data Engineering team. As an Analytics Engineer, you will play a pivotal role in advancing the maturity of our data organization. Working cross-functionally with Engineering, Product, Security, and business stakeholders, you’ll design, build, and own the core infrastructure and data models that power data-driven decision-making across the organization.

## Responsibilities

- Design, develop, and maintain scalable analytics data models that support reporting, business intelligence, product analytics, and operational decision-making.

- Build and manage trusted data pipelines and transformation workflows using modern analytics engineering practices.

- Partner with stakeholders across Engineering, Product, Design, Strategy & Operations, and AI Platform to understand business needs and translate them into effective data solutions.

- Establish clear definitions, metrics, dimensions, and data contracts to create consistency across teams and use cases.

- Develop reusable datasets and semantic models that enable self-service analytics and reduce duplicated work.

- Improve the reliability, performance, observability, and maintainability of analytics infrastructure.

- Implement data quality checks, testing, documentation, lineage, and monitoring for critical data assets.

- Collaborate with data engineers and platform teams to optimize data architecture, warehouse performance, and transformation workflows.

- Work with analysts, data scientists, and business partners to ensure data products are intuitive, discoverable, and fit for purpose.

- Help establish best practices for analytics engineering, including version control, code review, CI/CD, documentation, and deployment standards.

- Communicate technical concepts clearly to both technical and non-technical audiences.

## Requirements

- 4+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a related field.

- Strong SQL skills, including experience developing complex queries and dimensional data models.

- Experience building and maintaining analytics transformations using tools such as dbt or comparable frameworks.

- Proficiency in Python or another programming language used for data processing and automation.

- Experience working with modern cloud data warehouses such as Snowflake, Databricks, BigQuery, or Redshift.

- Strong understanding of data modeling concepts, including dimensional modeling, fact and dimension tables, slowly changing dimensions, and semantic layers.

- Experience implementing data quality testing, monitoring, documentation, and observability practices.

- Demonstrated ability to partner with cross-functional stakeholders and translate ambiguous business questions into scalable data solutions.

- Strong communication, problem-solving, and organizational skills.

- A thoughtful approach to data governance, security, privacy, and responsible use of data.

- Familiarity with data cataloging and lineage tools.

## Tech Stack

- Warehousing: Snowflake as the primary warehouse; BigQuery for GCP-native workloads

- Ingestion: Fivetran for SaaS-to-Snowflake pulls; Airflow (on AWS) for custom DAGs, Lambda-based extraction, and S3 staging

- Modeling: dbt for transformation and semantic layer definition

- Custom compute: Databricks for bespoke modeling work that doesn't fit cleanly into dbt/Snowflake

- Infrastructure: Terraform for managing Fivetran connections, GCP infrastructure, and AWS resources

- Version control & CI/CD: GitHub

- Consumption: Tableau dashboards; internal tools built on top of semantic data layers

## Skills

### Required
- SQL
- analytics engineering
- data engineering
- business intelligence engineering
- Python
- Snowflake
- Databricks
- BigQuery
- Redshift
- dbt
- data modeling
- dimensional modeling
- data quality testing
- monitoring
- documentation
- observability practices

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/zoominfo/jobs/8879302002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)