Data Engineer

WELL Health Technologies Corp

10d•Remote

About The Position

We are looking for a Data Engineer for the WELL Intelligence Platform. In this hands-on role, you will design, build, and operate reliable, secure, and scalable data pipelines and data products that power analytics, automation, and AI. This is a Snowflake-heavy position suited for a builder who can implement complex solutions, troubleshoot issues end-to-end, and continuously improve platform engineering quality. You will work under the architectural direction of the Senior Data Architect while contributing to design discussions, proposing implementation approaches, and delivering high-quality code that meets platform standards for governance, security, performance, and observability. This is an opportunity to influence the foundation of a modern Data & AI platform, set standards for data quality and governance, and make a measurable impact across analytics, automation, and AI initiatives. This is an existing, fully remote role based anywhere in Canada.

Requirements

You have in-depth engineering experience delivering production-grade data pipelines and data products in cloud environments (Azure and/or AWS).
You have a proven track record of building reliable, scalable solutions on modern cloud data platforms and operating them in production.
You bring advanced SQL skills, including complex query design and performance tuning, and strong proficiency in Python for data engineering workloads.
You have deep, hands-on experience with Snowflake, including data modelling, workload management, and performance and cost optimization, or equivalent experience with a modern cloud data warehouse.
You understand dimensional modelling principles, conformed entities, and normalization trade-offs.
You have experience designing robust pipelines, including incremental processing, CDC, backfills, idempotency, and handling late-arriving data.
You are familiar with transformation frameworks such as dbt or equivalent.
You understand data governance concepts, including lineage, cataloging, quality management, and stewardship.
You have experience working within Azure and/or AWS cloud ecosystems and understand modern cloud-native data architecture patterns.
You have hands-on experience with orchestration frameworks such as Airflow, ADF, or Dagster, and understand distributed compute paradigms, including Spark and Databricks, and when to leverage them.
You have exposure to eventing and streaming technologies such as Kafka, Kinesis, or Event Hubs, and understand the operational realities of hybrid batch-and-event-driven architectures.
You are proficient with Git, structured code reviews, automated testing strategies, and CI/CD pipelines.
You are familiar with Infrastructure-as-Code principles and can collaborate effectively with Cloud Engineering teams.
You implement observability best practices, including logging, monitoring, alerting, and operational dashboards to support production reliability.
You have experience implementing row- and column-level security, masking, tokenization, and secure data sharing patterns.
You have exposure to AI-enabling use cases, including building AI-ready datasets, feature engineering patterns, and controlled access mechanisms for advanced analytics.
You have professional communication skills and can build collaborative relationships within and across teams.
You are open to feedback and sharing knowledge.
You are driven, curious, and solution-oriented.