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- Full-time
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Coveo

Senior Data Analytics Developer

Montreal, QC, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: May 5, 2027
Experience: You have 5 years of experience in a similar role, with expertise in building data pipelines, data models, and analytics for large-scale distributed systems.
Posting language: English
Posted: Nov 6, 2026

Original job description

Build the data foundation powering Coveo's next generation of product innovation.

Are you passionate about building the data foundations that power innovative products? As a Senior Data Developer, you’ll help build and scale the data platform behind Coveo’s product. You’ll design the core data models and shared datasets that power product reporting, customer-facing insights, machine learning, and AI agents.

You’ll also strengthen data quality and pipeline reliability, working with dbt, Snowflake, Databricks, and Python to process hundreds of millions of events daily. Your work will directly support the development of data-driven product features, helping our teams turn complex data into meaningful product improvements.

Here is a glimpse of your responsibilities:

Work with product engineering to turn questions about how users interact with Coveo into well-defined data models.
Build and maintain pipelines that process hundreds of millions of events a day, with tests and monitoring to keep them reliable.
Design batch and streaming transformations, from incremental dbt models in Snowflake to PySpark Structured Streaming jobs in Databricks, and choose the right one for each use case based on latency, cost and data volume.
Take ownership of complex data engineering initiatives, proactively improving data reliability, performance and maintainability while sharing your expertise with teammates
Build AI agents that query our data models directly, and improve their answers by refining the models and definitions they rely on.

Here is what will qualify you for the role:

You have 5 years of experience in a similar role, with expertise in building data pipelines, data models, and analytics for large-scale distributed systems.
You possess a strong engineering background, with hands-on experience in Python, dbt, Snowflake and Databricks.
You have in-depth knowledge of SQL, ETL processes, data warehousing, and Data Lake architecture.
You have experience with automated testing frameworks and a commitment to code quality, including unit testing, integration testing, and code coverage metrics.
You excel at working collaboratively with cross-functional teams and possess exceptional written and verbal communication skills on both technical and non-technical subjects.
You have experience with cloud providers, ideally AWS.

What would make you stand out:

Experience with PySpark and structured streaming, particularly in a product development environment.
Experience with orchestrating complex workflows using tools such as Airflow, Dagster or Prefect.
Familiarity with infrastructure as code and with CI/CD tools such as Jenkins, Github Actions, etc to automate testing, deployment, and integration processes.
Hands-on experience with containerizing applications and managing them at scale using orchestration platforms.

Do you think you can bring this role to life? Send us your application, we want to hear from you!

Join the Coveolife!

We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background.

This job description was written by humans, assisted by AI. We may leverage technology in our hiring process to help us see the person behind the resume.

Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.

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More about this job

Responsibilities

Design and maintain scalable data models and reliable batch and streaming pipelines that process hundreds of millions of events daily, using tools such as dbt, Snowflake, Databricks, and Python. Partner with product engineering to support reporting, customer insights, machine learning, and AI agents while improving data quality, performance, and maintainability.

Requirements

Requires five years of relevant experience building data pipelines, models, and analytics for large-scale distributed systems, with hands-on expertise in Python, dbt, Snowflake, Databricks, SQL, ETL, and data warehousing. Candidates should also have experience with automated testing, cloud providers (ideally AWS), and cross-functional communication; PySpark streaming, workflow orchestration, infrastructure as code, CI/CD, and container orchestration are additional assets.

Skills

Data Engineering
Data Modeling
Python
SQL
dbt
Snowflake
Databricks
PySpark
Structured Streaming
ETL
Data Warehousing
Data Lake Architecture
Automated Testing
AWS
Workflow Orchestration
Infrastructure as Code

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Data Analytics
Data Platform
Data Models
Shared Datasets
Data Pipelines
Data Quality
Pipeline Reliability
Python
SQL
dbt
Snowflake
Databricks
PySpark
Structured Streaming
Batch Processing
Streaming Transformations
ETL
Data Warehousing
Data Lake Architecture
Automated Testing
Unit Testing
Integration Testing
Code Coverage
AWS
Airflow
Dagster
Prefect
Infrastructure as Code
CI/CD

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