Top AWS Jobs in Calgary

Lead backend engineering work for Affirm’s lakehouse infrastructure, delivering reliable, scalable distributed data systems. Own quarterly goals, guide engineers through ambiguous problems, collaborate with product and analytics stakeholders, improve technical standards, monitor system availability, support on-call operations, and mentor team members. The role focuses on large-scale data platforms and technologies including Iceberg, Flink, Airflow, Spark, Kafka, Snowflake, AWS, MySQL, Kubernetes, and Terraform.

Designs and builds secure, scalable systems protecting products, infrastructure, and customer data. Responsibilities include authentication and OAuth integrations, authorization platforms, BYOK capabilities, security tooling, cloud security controls, threat modeling, vulnerability remediation, and security testing. The role partners with engineering and product teams, establishes secure development practices, leads complex security projects, and mentors engineers.

Principal Full Stack Software Engineer responsible for guiding technical direction, designing large-scale SaaS features, and building secure, reliable distributed systems. The role involves collaborating across product, design, and engineering; evaluating technical trade-offs; debugging team inefficiencies; contributing to code reviews and complex fixes; mentoring engineers; and improving engineering practices around testing, performance, security, privacy, and service operations.

Build backend data and measurement systems connecting marketing acquisition activity to signup, conversion, and GMV outcomes. Develop reliable pipelines, identity and event data systems, attribution capabilities, and marketing technology integrations while incorporating privacy, consent, and consumer-data requirements. Lead engineers through ambiguous problems, own quarterly goals, improve system reliability and code quality, collaborate cross-functionally, and mentor team members.

Lead the design, scalability, reliability, and optimization of continuous integration systems, build pipelines, automated testing, deployment workflows, and developer productivity tooling. Improve feedback cycles, monitoring, alerting, incident response, and engineering enablement across the organization. Mentor CI engineers, establish CI/CD best practices, and align developer infrastructure with broader platform goals.

Develop backend tools and systems that improve batch development, testing, and reliability. Responsibilities include breaking projects into deliverable phases, collaborating with product and infrastructure teams, monitoring system metrics, supporting on-call operations, writing tested and extensible code, debugging, participating in code reviews, and contributing to engineering growth activities.

Build and launch scalable backend systems and APIs for Affirm’s partner and merchant integrations. Responsibilities include breaking projects into deliverable phases, collaborating with product, design, and analytics teams, monitoring service health, participating in on-call operations, debugging code, conducting code reviews, and supporting team development. The role requires backend development experience with Python or Kotlin, distributed systems knowledge, and familiarity with AWS, MySQL, and Kubernetes.

Build and scale Affirm’s managed cache platform using Redis and Valkey. Responsibilities include cluster migrations, capacity and shard planning, failover and replication, upgrades, self-service automation, monitoring, SLOs, incident response, and advising teams on caching strategy. The role also involves designing tested backend systems, collaborating across engineering and product teams, participating in on-call operations, and contributing to code reviews and team development.

Design and build backend APIs, microservices, and checkout platform components for Affirm’s financial products. Improve system performance, reliability, tooling, and engineering standards while collaborating across teams. Own components over their lifecycle, contribute to technical decisions, ship high-quality software at scale, and support peer development through communication and knowledge sharing.

Leads the technical direction and implementation of large-scale SaaS product features. Designs and builds secure, reliable, maintainable enterprise solutions using microservices and distributed systems. Collaborates cross-functionally on product strategy, debugs team inefficiencies, performs code reviews, resolves complex bugs, and improves engineering practices around testing, performance, security, and privacy. Mentors and coaches engineers while identifying organizational blockers and redundant efforts.

Designs and maintains reliable data pipelines and computed tables using SparkSQL and PySpark. Integrates IoT, product, customer, external, unstructured, and ML-related data into scalable data models supporting analytics, causal inference, model training, and dashboards. The role requires ETL development, data orchestration, API integration, strong data quality and uptime, and collaboration with Data Science, AI/ML, Analytics, and engineering teams. This is a remote position for candidates residing in Canada.

Build and scale reliable Snowflake data pipelines, ML pipelines, monitoring systems, and AI-driven agentic tooling that automates pipeline generation, testing, and maintenance. The role partners with analysts, data scientists, product teams, and analytics engineers to deliver scalable end-to-end data infrastructure for Babylist’s e-commerce platform.

Lead the design, development, and technical strategy for high-availability financial services supporting Affirm’s card loan platform. Build scalable APIs, data models, microservices, and event-driven systems; troubleshoot performance and reliability issues; collaborate cross-functionally on loan attribution and lifecycle requirements; and mentor engineers through technical guidance, design reviews, and code reviews.

Own the direction and implementation of Babylist’s personalization domain, including recommendation, search, feed models, custom embeddings, and shared representations. Take ambiguous problems from concept through production, owning architecture, deployment, monitoring, retraining, evaluation, and customer impact. Partner with product, design, and data, establish AI development standards, make cross-team technical decisions, and coach senior engineers while remaining hands-on with complex machine learning systems.

Own third-party risk management and business continuity programs while building production data pipelines, integrations, policy-as-code controls, continuous monitoring, and agentic AI workflows. The role requires defining technical direction, integrating imperfect data sources, automating evidence collection, and partnering across Security, Procurement, Resilience, and Engineering teams to improve governance and operational resilience.

Own the application end to end across React, Node.js, SQL, APIs, integrations, deployment, and production support. Design and implement scalable solutions, troubleshoot complex issues, make architecture and performance decisions, review code, mentor engineers, address technical debt and security concerns, and collaborate across Product, QA, DevOps, and Architecture throughout the SDLC.

Owns end-to-end DevOps, cloud infrastructure, CI/CD, Kubernetes, Infrastructure as Code, monitoring, security, reliability, and production operations. The role designs automated deployment processes, manages cloud environments, troubleshoots complex infrastructure and networking issues, implements observability and disaster recovery, optimizes cloud costs, and guides engineering teams on secure, scalable DevOps practices.

Build and scale AI-enabled developer experience, CI/CD, deployment safeguards, observability, and automated response systems. The role focuses on making software delivery autonomous, safe, reliable, and easier for engineering teams to adopt. Responsibilities include architecting enterprise-scale platforms, orchestrating AI agents, reducing technical debt and operational toil, partnering with product engineering teams, and establishing AI-native SDLC workflows. The engineer will also provide technical leadership and turn emerging AI capabilities into production-ready internal platforms.

Build and operate database and storage platform software, including services, APIs, developer tools, migrations, and lifecycle automation. Solve database scaling, performance, reliability, and availability problems across distributed systems, cloud infrastructure, and backend services. Partner with engineering teams on schemas and queries, lead technical projects, modernize platforms, participate in incident response, and use AI-assisted tools in development.

Build and operate full-stack compliance platforms for transaction search, entity labeling, ingestion, and workflow automation. Responsibilities include designing microservices and event-driven systems, writing tested code, improving sensitive financial data quality, building self-service tools and high-volume pipelines, partnering with Compliance and Risk teams, and participating in on-call operations. The role also involves using AI-powered development tools, reviewing code, and supporting engineering standards.

Develop and scale backend streaming and data infrastructure using technologies such as Kafka, Flink, AWS, and Kubernetes. Design, launch, test, and maintain distributed systems, monitor service availability, participate in on-call support, collaborate with product and engineering stakeholders, review code, and contribute to technical planning and team development.

Lead technical strategy and architecture for a backend search team building highly available distributed systems, recommendations, and discovery experiences. Partner with product, design, and analytics; establish engineering standards, operational processes, monitoring, testing, and on-call practices. Drive major technical initiatives, mentor engineers, communicate technical direction, and support scalable consumer and merchant experiences.

Build and operate database and storage platform software, including services, APIs, and developer tools for provisioning, migrations, upgrades, and lifecycle management. Solve scaling, performance, reliability, and data correctness challenges across databases, distributed systems, cloud infrastructure, and networking. Partner with engineering teams on schemas and platform adoption, lead technical projects through rollout, participate in on-call response, and use AI-assisted tools in development.

Architect, build, and operate large-scale relational and distributed SQL database infrastructure. Responsibilities include control-plane automation, provisioning, failover, backups, upgrades, zero-downtime migrations, Kubernetes networking, connection proxy optimization, reliability monitoring, capacity planning, and on-call support. The role also involves technical leadership, roadmap ownership, code quality standards, mentoring, and cross-functional collaboration.

Build and operate end-to-end full-stack features for Loom billing, subscriptions, integrations, and platform migrations. Develop responsive React interfaces, scalable backend APIs and microservices, payment and identity integrations, and reliable cloud-based systems. Responsibilities include observability, monitoring, testing, code reviews, documentation, security, performance optimization, and participation in Agile ceremonies and technical design reviews.