Senior Data & Analytics Engineer

Overview

Join to apply for the Senior Data & Analytics Engineer role at Wagepoint
.

This range is provided by Wagepoint. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

CA$/yr - CA$/yr

Who We Are:

At Wagepoint, we’re good people. We’re a diverse team who bring our backgrounds, ideas, experiences and cultures together to make payroll magic. We serve thousands of small business owners across Canada who rely on our payroll software to pay their employees and process their payroll taxes.

We’re growing and looking for more awesome people to join our team. We share a commitment to our customers and to delivering high-impact work. Wagepoint is a remote company and values collaboration, accountability and continuous learning.

If you are the kind of person who has always wanted to make a difference and be heard at work, Wagepoint will give you plenty of opportunity to do just that.

We’re looking for a talented Senior Data & Analytics Engineer who tackles complex data challenges and builds scalable, high-performance data systems. You’ll shape how Wagepoint collects, transforms, and visualizes data to drive smarter business decisions across the organization.

You’ll design and implement data pipelines, architect analytical dashboards, and ensure our data systems are fast, reliable, and secure. You’ll report directly to our Engineering leadership team and collaborate with Analytics, Product, and Business Intelligence partners.

• Design, develop, and optimize scalable, cloud-native data pipelines capable of processing millions of records per day.
• Build automated ETL/ELT workflows and validation layers that ensure high data quality and minimal manual intervention.
• Develop and maintain data models, data lakes, and warehouses (primarily in Azure) that support analytics, BI, and AI/ML workloads.
• Create and optimize analytical dashboards and reports in Power BI or Tableau, ensuring fast query performance and low-latency reporting.
• Standardize and document data definitions, maintain an up-to-date data dictionary
  , and ensure consistency across all sources.
• Monitor and tune data workflows, improving efficiency and scalability.
• Implement robust data validation frameworks and real-time monitoring to identify and resolve quality issues at the source.
• Partner cross-functionally with data scientists, analysts, and engineers to deliver accessible, trusted data that supports business needs.

• 7+ years of experience in data engineering, ETL/ELT development, and analytics reporting
  .
• Proven expertise in tools such as Apache Airflow, dbt, Spark, Databricks, Snowflake, and Kafka
  .
• Advanced proficiency in Python and SQL for data transformation and analysis.
• Strong experience working with cloud platforms (especially Azure) — Data Lake, Synapse, CosmosDB, etc.
• Deep understanding of data modeling, warehousing, and scalable architecture
  .
• Experience with containerization and CI/CD (Docker, Kubernetes).
• Strong grasp of data governance, security best practices
  , and compliance frameworks.
• Demonstrated ability to design for monitoring, testing automation, and operational excellence
  .
• Experience supporting BI tools like Power BI, Tableau, or D3.js.
• Exceptional troubleshooting, problem-solving, and optimization skills.
• You’ve implemented or scaled real-time data pipelines for analytics or AI/ML.
• You’re passionate about data automation, observability, and quality frameworks
  .
• You’ve built metadata repositories or data lineage systems
  .
• You thrive in cross-functional environments and love enabling self-serve analytics for non-technical users.
• You’re a Power BI or Tableau guru who enjoys designing visually engaging and…