At Wave we help small businesses to thrive so the heart of our communities beats stronger. We work in an environment buzzing with creative energy and inspiration. No matter where you are or how you get the job done you have what you need to be successful and connected. The mark of true success at Wave is the ability to be bold learn quickly and share your knowledge generously.
Reporting to the Senior Manager of AI & Data Platform as a Senior Data Engineer you will be building tools and infrastructure to support the efforts of the Data Products and Insights & Innovation teams and the business as a whole.
Were looking for a talented curious selfstarter who is driven to solve complex problems and can juggle multiple domains and stakeholders. This highly technical individual will collaborate with all levels of the Data and AI team as well as various engineering teams to develop data solutions scale our data infrastructure and advance Wave to the next stage in our transformation as a datacentric organization.
This role is for someone with proven experience in complicated product environments. Strong communication skills are a must to bridge the gap between technical and nontechnical audiences across a spectrum of data maturity.
At Wave youll have the chance to grow and thrive by building scalable data infrastructure enhancing a modern data stack and contributing to highimpact projects that empower insights and innovation across the company.
Heres How You Make an Impact:
Youre a builder. Youll be responsible for designing building and deploying the components of a modern data stack including CDC ingestion (using Meltano or similar tools) a centralized Iceberg data lake and a variety of batch incremental and streambased pipelines.
Youll make things better. You enjoy the challenge of helping build and manage a faulttolerant data platform that scales economically while balancing innovation with operational stability by maintaining legacy Python ELT scripts and accelerating the transition to dbt models in Redshift Snowflake or DataBricks.
Youre all about collaboration and relationships. You will collaborate within a crossfunctional team in planning and rolling out data infrastructure and processing pipelines that serve workloads across analytics machine learning and GenAI services. You enjoy working with different teams across Wave and helping them succeed by ensuring that their data analytics and AI insights are reliably delivered.
Youre selfmotivated and can work autonomously. We count on you to thrive in ambiguous conditions by independently identifying opportunities to optimize pipelines and improve data workflows under tight deadlines.
You will resolve and mitigate incidents. You will respond to alerts and proactively implement monitoring solutions to minimize future incidents ensuring high availability and reliability of data systems.
Youre a strong communicator. As a data practitioner youll have people coming to you for technical assistance and your outstanding ability to listen and communicate with people will reassure them as you help answer their concerns.
You love helping customers. You will assess existing systems optimize data accessibility and provide innovative solutions to help internal teams surface actionable insights that enhance external customer satisfaction.
You Thrive Here By Possessing the Following:
Data Engineering Expertise: Bring 6 years of experience in building data pipelines and managing a secure modern data stack. This includes CDC streaming ingestion using tools like Meltano or similar for data ingestion workflows that support AI/ML workloads and a curated data warehouse in Redshift Snowflake or DataBricks.
AWS Cloud Proficiency: At least 3 years of experience working with AWS cloud infrastructure including Kafka (MSK) Spark / AWS Glue and infrastructure as code (IaC) using Terraform.
Strong Coding Skills: Write and review highquality maintainable code that enhances the reliability and scalability of our data platform. We use Python SQL and dbt extensively and you should be comfortable leveraging thirdparty frameworks to accelerate development.
Data Lake Development: Prior experience building data lakes on S3 using Apache Iceberg with Parquet Avro JSON and CSV file formats.
Workflow Automation: Experience with Airflow or similar orchestration systems to build and manage multistage workflows that automate and orchestrate data processing pipelines.
Data Governance Knowledge: Familiarity with data governance practices including data quality lineage and privacy as well as experience using cataloging tools to enhance discoverability and compliance.
CI/CD Best Practices: Experience developing and deploying data pipeline solutions using CI/CD best practices to ensure reliability and scalability.
Data Integration Tools: Working knowledge of tools such as Stitch and Segment CDP for integrating diverse data sources into a cohesive ecosystem.
Analytical and ML Tools Expertise: Knowledge and practical experience with Athena Redshift or Sagemaker Feature Store to support analytical and machine learning workflows is a definite bonus!
Succeeding at Wave: At Wave youll have the chance to grow and thrive by building scalable data infrastructure enhancing a modern data stack and contributing to highimpact projects that empower insights and innovation across the company. Whether collaborating in our vibrant downtown Toronto hub or working remotely youll have the flexibility to shape your journey and make a lasting impact on Waves datadriven future. At Wave we value diverse perspectives and encourage open respectful feedback fostering an inclusive environment where innovation flourishes and every team member has the opportunity to grow.
At Wave we value diversity of perspective. Your unique experience enriches our organization. We welcome applicants from all backgrounds. Lets talk about how you can thrive here!
Wave is committed to providing an inclusive and accessible candidate experience. If you require accommodations during the recruitment process please let us know by emailing We will work with you to meet your needs.
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