Staff Data Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Collaborate with business stakeholders to recognize and prioritize opportunities and initiatives driven by data.

• Design, construct, and sustain scalable data pipelines that support analytics, reporting, product development, and operational use cases.

• Develop, test, and enhance dbt models in accordance with data modeling best practices.

• Manage and support orchestration platforms such as Airflow, along with experience in Dagster.

• Create and implement dimensional, semantic, and analytical data models for self-service analytics and business intelligence.

• Influence data architecture decisions and set engineering standards and best practices.

• Collaborate with data engineers and platform teams to enhance the reliability, scalability, and performance of the data ecosystem.

• Develop and uphold data quality frameworks, testing strategies, and observability solutions.

• Facilitate governance through documentation, metadata management, lineage tracking, and data ownership practices.

• Conduct complex analyses and deliver actionable recommendations to business stakeholders.

• Oversee team analysis to ensure data accuracy, consistency, and business relevance.

• Advocate for the adoption of data exploration and self-service analytics tools.

• Lead technical design reviews and mentor team members through code reviews, architectural guidance, and knowledge sharing.

• Assist in hiring, onboarding, mentoring, and professional development of data engineers.

• Engage in incident response, root cause analysis, and continuous improvement efforts for critical data platform issues.

• Perform additional duties as necessary.

⛳️ Requirements

• Bachelor's degree in Computer Science, Data Engineering, Statistics, Information Systems, Business, or a related field.

• Over 8 years of experience in data engineering, analytics engineering, or a related field.

• Practical expertise with BigQuery, dbt, Airflow, Python, SQL, and modern cloud data platforms.

• Strong grasp of data warehousing concepts, ETL/ELT design patterns, and dimensional modeling.

• Experience in building and optimizing scalable data transformation pipelines within cloud environments.

• Familiarity with Google Cloud Platform services such as BigQuery, Cloud Storage, Pub/Sub, and Cloud Composer.

• Exposure to Azure data platforms and services is advantageous.

• Proficiency in Git-based development workflows, CI/CD pipelines, and software engineering best practices.

• Experience in implementing automated testing, monitoring, and data observability solutions.

• Familiarity with data visualization and exploration tools like Looker, Mode, Tableau, or similar platforms.

• Exceptional communication and stakeholder management skills, with the capability to translate business requirements into scalable technical solutions.

• Demonstrated ability to lead complex projects and influence technical direction across multiple teams.

🏝️ Benefits

• Competitive compensation package.

• Enjoyable, relaxed work environment.

• Reimbursements for education and conferences.

• Opportunities for career advancement and mentoring others.

• Bonus eligibility for most non-sales roles.

• Exceptional benefits package with options and support for physical, financial, and emotional wellbeing.