Scan your resume against ATS criteria for this Senior Data Engineer - Data Performance and Tooling role at jobgether.
This role is focused on building the foundational data infrastructure that enables a fast-growing SaaS organization to operate, analyze, and make better decisions at scale.
You will take end-to-end ownership of critical data infrastructure projects, from architecture and implementation through production operations and continuous improvement.
The position combines data engineering, cloud infrastructure, streaming systems, security, and performance optimization in a highly technical environment.
You will work closely with analytics, product, platform, and engineering teams to translate business needs into reliable and scalable data solutions.
A key part of the role is helping shape data strategy, governance, and accessibility as the organization continues to grow.
You will also contribute to modernizing data capabilities through technologies such as AWS, Apache Iceberg, Snowflake, Kafka, and infrastructure as code.
This is an opportunity to make a broad technical impact while using AI thoughtfully to accelerate routine engineering work and focus on complex technical challenges.
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 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.
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.
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.
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!
https://jobgether.com/how-jobgether-works Why Apply Through Jobgether?
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How to apply for Senior Data Engineer - Data Performance and Tooling at jobgether?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
The salary for this role is $121,600 per annum.
What experience is required?
5+ years of experience is required.
Is this position still open?
Yes, currently active and accepting applications.
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Senior Data Engineer - Data Performance and Tooling
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