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Mid LevelFull-timePythonRustAWSTerraformMachine LearningCI/CDAIMLData
Salary Range
CA$101,000 - CA$113,000 /year
About the Role
We are looking for a Data Engineer to join our team at Wave, a company that helps small businesses thrive. This role involves building tools and infrastructure to support data products and insights teams, driving Wave's transformation as a data-centric organization.
Key Responsibilities
- →Design, build, and deploy components of a modern data platform, including CDC-based ingestion using Debezium and Kafka, a centralized Hudi-based data lake, and various data pipelines.
- →Maintain and enhance the Amazon Redshift warehouse and legacy Python ELT pipelines while transitioning to a Databricks and dbt-based analytics environment.
- →Build fault-tolerant, scalable, and cost-efficient data systems, improving observability, performance, and reliability.
- →Partner with cross-functional teams to design and deliver data infrastructure supporting analytics, machine learning, and GenAI use cases.
- →Work autonomously to optimize data pipelines and improve workflows under tight timelines.
- →Respond to PagerDuty alerts, troubleshoot incidents, and implement monitoring to maintain high availability.
- →Provide technical guidance to colleagues, clearly communicating complex concepts.
- →Assess existing systems, improve data accessibility, and deliver solutions for actionable insights.
Requirements
- ✓3+ years of experience building data pipelines and managing a secure, modern data stack.
- ✓At least 3 years of experience working with AWS cloud infrastructure, including Kafka (MSK), Spark / AWS Glue, and Terraform.
- ✓Fluency in SQL and strong understanding of data modelling principles for both OLTP and OLAP.
- ✓Experience developing or maintaining a production data system on Databricks.
- ✓Experience writing and reviewing high-quality code using Python, SQL, and dbt.
- ✓Prior experience building data lakes on S3 using Apache Hudi with various file formats.
- ✓Experience developing and deploying data pipeline solutions using CI/CD best practices.
