Description:

The Senior Data Engineer position is located in Toronto, Ontario, and is a full-time remote role within the Data & AI team.
The role involves building tools and infrastructure to support the Data Products and Insights & Innovation teams, as well as the business as a whole.
The ideal candidate is a talented, curious self-starter who is driven to solve complex problems and can manage multiple domains and stakeholders.
Responsibilities include designing, building, and deploying components of a modern data stack, including CDC ingestion using Debezium, a centralized Hudi data lake, and various data pipelines.
The engineer will help manage a fault-tolerant data platform, maintain legacy Python ELT scripts, and transition to dbt models in Redshift.
Collaboration with cross-functional teams is essential to plan and roll out data infrastructure and processing pipelines for analytics, machine learning, and GenAI services.
The role requires self-motivation and the ability to work autonomously, identifying opportunities to optimize pipelines and improve data workflows.
The engineer will respond to PagerDuty alerts, implement monitoring solutions, and ensure high availability and reliability of data systems.
Strong communication skills are necessary to assist technical and non-technical audiences and to help internal teams surface actionable insights for customer satisfaction.

Requirements:

Candidates must have 3+ years of experience in building data pipelines and managing a secure, modern data stack, including CDC streaming ingestion using tools like Debezium into a Hudi data lake.
At least 3 years of experience with AWS cloud infrastructure, including Kafka (MSK), Spark/AWS Glue, and infrastructure as code (IaC) using Terraform is required.
Strong coding skills in Python, SQL, and dbt are necessary, with the ability to write and review high-quality, maintainable code.
Prior experience in building data lakes on S3 using Apache Hudi with various file formats (Parquet, Avro, JSON, CSV) is essential.
Candidates should have experience in building and managing multi-stage workflows using serverless Lambdas and AWS Step Functions.
Familiarity with data governance practices, including data quality, lineage, and privacy, is required, along with experience using cataloging tools.
Experience with CI/CD best practices for developing and deploying data pipeline solutions is necessary.
Working knowledge of data integration tools such as Stitch and Segment CDP is required.
Knowledge and practical experience with analytical and ML tools like Athena, Redshift, or Sagemaker Feature Store is a bonus.

Employees have the flexibility to work from the office in downtown Toronto or remotely, depending on their preference.
The company invests in employee health and wellness, offering comprehensive benefits that address body, mind, and soul.
There are diverse learning experiences, educational allowances, and mentorship opportunities to support personal and professional growth.
Fair compensation and various office perks are provided, along with the expected benefits of a growing tech company.
Wave fosters an inclusive culture that values diverse perspectives and encourages open feedback, ensuring every team member has the opportunity to grow.
The company has been recognized as one of Canada's Top Ten Most Admired Corporate Cultures and a great place to work in various categories.