Senior Software Developer at TELUS Health, designing and developing pharmacy management tools. Integrating AI - driven solutions for healthcare delivery with a collaborative engineering team.
About the role
- Staff Software Engineer developing and evolving the enterprise data platform at RB Global. Leading architecture and engineering practices across the data team.
Responsibilities
- Define and drive the technical vision for the enterprise data platform, making key architecture and technology decisions that impact the entire data organization.
- Lead the design of scalable, resilient ETL/ELT data pipelines using dbt, Python, and SQL, establishing patterns and best practices for the team to follow.
- Architect and optimize data models and transformations within cloud data warehouses (Snowflake, BigQuery), ensuring performance, cost-efficiency, and maintainability.
- Architect and standardize the use of Snowflake semantic views to establish a governed semantic layer, ensuring consistent metric definitions across Power BI, Tableau, and Looker.
- Own the design and evolution of workflow orchestration using Apache Airflow (AWS MWAA), driving improvements in reliability and developer experience.
- Lead the strategy for real-time streaming ingestion using Kafka and Snowpipe Streaming, evaluating trade-offs and guiding implementation.
- Drive CI/CD strategy and Infrastructure as Code practices using Terraform, CircleCI, Harness, and GitHub Actions — raising the bar for deployment reliability and velocity.
- Champion and advance data modeling standards (dimensional modeling, star/snowflake schemas, data vault) across the platform.
- Define and implement observability strategy using Datadog, including SLOs, alerting, and dashboarding for pipeline and platform health.
- Lead the adoption of AI-driven development tools and practices across the team, identifying high-impact opportunities to improve engineering productivity, code quality, and pipeline reliability.
- Define and operationalize data governance metrics — including data quality scores, lineage coverage, ownership accountability, and policy adherence — to measure and continuously improve platform trustworthiness.
- Lead investigation and resolution of complex data issues by analyzing end-to-end data lineage, identifying root causes, and driving systemic fixes to ensure the accuracy and trustworthiness of critical business metrics.
- Establish and enforce data quality, governance, and lineage standards across the platform.
- Mentor and support the growth of junior, intermediate, and senior engineers through knowledge sharing, pairing, technical guidance, and feedback.
- Collaborate with data architects, business analysts, engineering leadership, and cross-functional stakeholders to align technical strategy with business objectives.
- Partner with Engineering Managers to evaluate team performance, provide input for annual reviews, and participate in hiring initiatives.
- Support and improve data consumption layers including Power BI, Tableau, and Looker.
- Drive engineering best practices including code reviews, technical documentation, incident response processes, and post-mortems.
- Collaborate with other Staff and Sr. Staff Engineers to create a community of practice and an overall organizational technical strategy for business success.
- Influence and publish within the organization and industry to effect positive change in data engineering strategy and advance the craft of data platform development worldwide.
- Perform other duties and responsibilities as assigned in support of organizational priorities.
Requirements
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- 10+ years of experience in data engineering or software engineering, with at least 3+ years operating at a senior/staff level.
- Strong proficiency in Python (required) and SQL, with a solid foundation in object-oriented programming; experience with additional languages such as Java or Scala is a plus.
- Expert-level knowledge of cloud data warehouses (e.g., Snowflake, BigQuery) — Snowflake experience highly preferred, including semantic views, access policies, and governance capabilities.
- Proven track record of designing and scaling data platforms in production environments.
- Deep experience with dbt for data transformation at scale.
- Strong expertise in data modeling — dimensional modeling, star/snowflake schemas, data vault.
- Extensive experience with workflow orchestration tools (Apache Airflow preferred).
- Strong understanding of streaming technologies (Apache Kafka, Snowpipe) and event-driven architectures.
- Experience with AWS services (S3, MWAA, Glue) in production data environments.
- Proficiency with Infrastructure as Code (Terraform) and CI/CD tools (CircleCI, Harness, GitHub Actions).
- Experience with Datadog or similar monitoring and observability platforms, including defining SLOs and alerting strategies.
- Demonstrated ability to mentor engineers, lead design reviews, and influence technical direction without direct authority.
- Strong communication and collaboration skills, with the ability to work effectively in a hybrid team environment.
- Proficiency with Git/GitHub and modern development workflows.
- Strong advocate for AI-driven development tools and methodologies.
- Familiarity with BI tools such as Power BI, Tableau, or Looker/LookML.
- Experience with data governance and cataloging tools (Horizon Catalog or Select Star).
- Knowledge of HashiCorp Vault or secrets management solutions.
- Experience with data quality/testing frameworks.
- Experience contributing to or leading technical RFCs and architecture decision records (ADRs).
Benefits
- Health insurance
- Retirement plans
- Professional development opportunities
- 15 days of PTO each year
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