Senior Analytics Engineer

Toronto, Ontario, Canada

Live, first seen by us 21 days ago

Pay: Pay not listed
Work setting: Not stated
Employment: Not stated

What you’ll work on

Full posting

Design and maintain scalable analytics data models for reporting and BI
Build and manage trusted data pipelines and transformation workflows
Develop reusable datasets and semantic models for self-service analytics
Implement data quality checks, testing, documentation, and lineage
Establish metric definitions and data contracts across teams

From the employer’s posting

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.

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

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

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

About ZoomInfo Technologies

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.

In the employer’s words · Read in context

Apply at ZoomInfo Technologies

Posting record

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Status in our records: Live
First seen by us: Oct 13, 202621 days ago
Recorded sightings: 35
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 21

Similar jobs usually come down between day 6 and day 47.

From 1,409 similar postings that came down. Coming down is not always a hire.

ZoomInfo Technologies is hiring

12 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring has slowed
Its jobs tend to stay up a long time
8% of open jobs were reposted

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
AWS
BigQuery
Databricks
dbt
Fivetran
GCP
Redshift
S3
Snowflake
Tableau
Terraform
Airflow

Where the posting names them

- 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.

- 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.

- 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

- 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.

Our 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

- 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.

- 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

- Version control & CI/CD: GitHub - Consumption: Tableau dashboards; internal tools built on top of semantic data layers #LI-JH1 #LI-Remote

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About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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.

We are seeking an experienced Senior Analytics Engineer to join the Enterprise Data Engineering team at ZoomInfo.

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.

What You’ll Do

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.

What You’ll Bring

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.

Our 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

#LI-JH1 #LI-Remote

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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