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Senior Data Analytics Developer

  • Montreal, QC, Canada

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Job details

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

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.

More about this job

Responsibilities

You will design and maintain scalable data models and pipelines to support product reporting, machine learning, and AI agents. Additionally, you will collaborate with engineering teams to process large-scale event data and improve data reliability and performance.

Requirements

The role requires 5 years of experience in data engineering, specifically with Python, dbt, Snowflake, and Databricks. Candidates must possess strong knowledge of SQL, ETL processes, and automated testing frameworks within distributed systems.

Skills

  • Python
  • Dbt
  • Snowflake
  • Databricks
  • SQL
  • ETL
  • Data Warehousing
  • Data Lake
  • PySpark
  • Structured Streaming
  • Automated Testing
  • Data Modeling
  • Cloud Computing
  • AWS
  • CI/CD
  • Data Engineering

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Software
  • Engineering

Keywords

  • Data Analytics
  • Data Platform
  • Data Modeling
  • Python
  • Dbt
  • Snowflake
  • Databricks
  • PySpark
  • Structured Streaming
  • ETL
  • Data Warehousing
  • Data Lake
  • AWS
  • CI/CD
  • Jenkins
  • Github Actions
  • Airflow
  • Dagster
  • Prefect
  • Unit Testing
  • Integration Testing
  • Distributed Systems
  • AI Agents
  • Machine Learning
  • Data Reliability
  • Infrastructure As Code
  • Containerization
  • Product Engineering
  • Data Pipeline
  • Analytics

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