Senior Data Engineer - Data Performance and Tooling
Accountabilities: Design, deploy, and operate robust production-grade data infrastructure that can scale with organizational growth while balancing innovation, performance, operational stability, and reliability.
Contribute to the architecture, implementation, and ongoing maintenance of a secure and centralized data lake, establishing scalable foundations for analytics, reporting, product development, and business intelligence.
Design and build high-performance streaming applications and data pipelines that provide reliable, timely access to critical information across the organization.
Help define and implement strong security controls and governance practices for data infrastructure, ensuring that data remains secure, accessible, and appropriately managed.
Own infrastructure projects throughout their complete lifecycle, including technical design, implementation, production deployment, monitoring, documentation, operational runbooks, and knowledge transfer.
Partner closely with analytics, product, platform, and engineering teams to understand their data needs, translate requirements into technical solutions, and continuously improve systems based on real-world usage and feedback.
Apply strong data engineering practices to optimize pipelines, data models, queries, and infrastructure performance while identifying opportunities to improve reliability and efficiency.
Use AI tools strategically to accelerate repetitive infrastructure activities such as documentation, technical research, boilerplate development, and knowledge synthesis, allowing greater focus on complex engineering decisions.
Communicate technical decisions, architectural trade-offs, and infrastructure considerations clearly to both engineering teams and non-technical stakeholders.
Requirements:
Bring 5+ years of professional experience working with production data infrastructure, including hands-on experience deploying, maintaining, and improving systems within SaaS, technology, or data-intensive environments.
Demonstrate strong SQL and data warehouse fundamentals, including experience with ETL/ELT patterns, schema design, query optimization, data modeling, and performance troubleshooting.
Have hands-on experience with AWS services and infrastructure-as-code practices, including technologies such as Amazon MSK, AWS Glue, and Terraform.
Bring experience working with modern data lake and data warehouse technologies, particularly Apache Iceberg and Snowflake.
Have practical experience implementing database replication and change data capture pipelines using technologies such as Kafka, Debezium, Flink, Spark, or comparable technologies.
Demonstrate a proven ability to own infrastructure initiatives end-to-end, including designing systems, deploying them to production, operating them reliably, and iterating based on feedback and evolving requirements.
Possess strong problem-solving and systems-thinking skills, with the ability to make thoughtful technical trade-offs between speed, scalability, reliability, security, and maintainability.
Be comfortable communicating complex technical concepts to engineering and non-technical stakeholders, translating infrastructure considerations into clear business and operational implications.
Experience working with Ruby on Rails monolithic applications is considered an additional advantage.
Candidates who do not meet every listed qualification but can demonstrate strong relevant experience and enthusiasm for the role are encouraged to apply.
Benefits:
Competitive annual salary range of CAD $121,600–$190,000, with compensation designed to reflect professional growth, increasing expertise, and contribution over time.
Typical starting compensation of approximately CAD $144,400 for candidates joining at the accomplished level, with individual offers determined according to skills and experience.
Equity participation through a stock option plan, providing an opportunity to share in the long-term growth of the organization.
Regular career development conversations with management and a compensation approach designed to recognize increasing expertise and meaningful contributions.
Comprehensive benefits package designed to support employees across health, wellbeing, financial security, and other areas.
Remote-first work environment for team members based in Canada, with opportunities to collaborate across a geographically distributed organization.
Opportunity to work on foundational data infrastructure supporting a high-growth SaaS platform with a large and active customer and practitioner community.
Exposure to modern cloud, data, streaming, security, and AI technologies, with encouragement to experiment, learn, and apply new approaches.
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
#LI-CL1