Senior Software Engineer, Catalog Store

Accountabilities:

Lead the design, development, deployment, and operation of critical backend services and distributed storage systems, including Go-based RPC services, PostgreSQL clusters, and in-memory key-value stores.
Own the performance, scalability, and reliability of self-hosted PostgreSQL infrastructure on AWS EC2, including database sharding, replication, capacity planning, backup and recovery strategies, schema optimization, indexing, and infrastructure upgrades.
Drive the development and production adoption of new datastore technologies, overseeing data ingestion, freshness, API migrations, shadow testing, staged rollouts, and legacy system deprecation.
Design, optimize, and maintain Temporal-based ingestion workflows to ensure catalog data remains accurate, fresh, reliable, and observable.
Establish and improve engineering best practices through technical design documentation, architectural decisions, code reviews, and collaboration with partner engineering teams.
Strengthen system reliability through observability, service-level objectives (SLOs), automation, operational documentation, and proactive performance improvements.
Participate in on-call rotations, lead incident response activities, and implement follow-up improvements to prevent recurring issues.
Mentor and support other engineers, contribute to onboarding, and promote high standards of code quality, technical excellence, and knowledge sharing.
Explore and leverage AI-powered development tools to improve engineering productivity, research, implementation, and operational efficiency.
Requirements:
At least 5 years of professional software engineering experience building and operating backend services or distributed systems in large-scale cloud environments.
Strong production experience with Go, or extensive experience with another backend or systems programming language such as Java, C++, or Rust, combined with a willingness to work primarily with Go.
Hands-on production experience with PostgreSQL or another relational database, including data modeling, schema and index design, query optimization, replication, backups, and recovery.
Solid understanding of distributed systems architecture, with demonstrated experience designing for scalability, reliability, performance, caching, and low-latency data access.
Proven ability to independently lead complex engineering projects from problem definition and technical design through implementation, production rollout, and ongoing operations.
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience.
Experience working with AWS or another major cloud provider, including services such as EC2 and S3, and infrastructure-as-code tools such as Terraform.
Familiarity with production operations, including monitoring, metrics, logging, distributed tracing, on-call responsibilities, incident management, and post-incident reviews.
Experience developing or operating high-throughput, low-latency RPC services, using gRPC or similar technologies.
Knowledge of self-hosted database infrastructure, including sharded or replicated clusters, fleet management, and infrastructure automation.
Strong communication and collaboration skills, with the ability to write clear technical documentation, influence architectural decisions, and align stakeholders across teams.
Demonstrated ability to balance urgency, technical quality, and pragmatic decision-making in a fast-paced engineering environment.
Experience leading database or platform migrations with minimal or zero downtime, using techniques such as dual writes, shadow reads, backfills, and gradual traffic migration.
Familiarity with key-value and in-memory datastores such as Redis, Valkey, or Memcached, and distributed SQL databases such as Yugabyte or CockroachDB.
Knowledge of workflow orchestration platforms such as Temporal or data platforms such as Snowflake.
A track record of delivering measurable improvements in system latency, availability, infrastructure efficiency, or cloud costs.
Additional assets:
Experience mentoring engineers and improving engineering standards through constructive code and design reviews.
Experience using AI-powered tools to accelerate software development and operations or building AI-assisted engineering solutions.
Familiarity with technologies such as Python, Ruby, Rust, PostgreSQL, Redis, Valkey, Memcached, Temporal, Snowflake, S3, Terraform, Datadog, and Sentry.
Benefits:
Competitive compensation: Annual base salary ranging from CAD 168,000 to CAD 177,500, depending on experience, skills, and permanent work location.
Equity compensation: Eligibility for a new-hire equity grant and recurring annual equity refresh grants.
Remote flexibility: Remote-first working arrangements for eligible employees based in Ontario, Alberta, British Columbia, or Nova Scotia.
Flexible working environment: Freedom to choose where you work, whether from home, an office, or another suitable location.
Team connection: Opportunities to participate in regular in-person events and team-building activities.
Healthcare and employee benefits: Access to a comprehensive benefits package designed to support employee well-being.
Professional development: Opportunities to work with modern distributed systems, cloud infrastructure, emerging datastore technologies, and AI-powered engineering tools.
Technical ownership: The opportunity to lead high-impact projects, influence architectural decisions, and shape critical infrastructure at scale.