Principal Site Reliability Engineer responsible for AWS infrastructure and reliability engineering. Collaborating across teams to enhance platform performance and security practices.
About the role
- DevOps Engineer automating delivery pipelines for Journey Capital, a leading online lender in Canada. Focus on CI/CD, cloud infrastructure, and enhancing engineering productivity through automation.
Responsibilities
- Accelerate Automation & Delivery Velocity: Replace manual/semi-automated steps with end-to-end automation across build, test, deploy, environment provisioning, and operational runbooks.
- Identify SDLC bottlenecks with DEV, QA, Salesforce and data teams; deliver automation that measurably improves cycle time, deployment frequency, and change failure rate.
- Establish reusable patterns (Jenkins shared libraries, IaC modules, testing harnesses) to scale automation across teams.
- CI/CD Modernization & Orchestration: Enhance Jenkins/Bitbucket (& Gearset for Salesforce) pipelines to support multi-language builds (Java, JS/TS, Python, Apex), artifact flow through Nexus, and promotion across dev/UAT/prod with automated rollback and environment parity checks.
- Integrate automated test suites (unit, integration, e2e, contract) as quality gates; surface signal early and reduce reliance on manual testing.
- Implement release strategies (blue/green, canary, rolling) for EC2/ECS/EKS workloads.
- AWS Infrastructure Automation: Provision and govern AWS resources (VPC, EC2, ECS, EKS, ELB, S3, RDS [Postgres/MySQL], IAM, CloudWatch/CloudTrail, KMS, SSM) with Terraform/CloudFormation and PR-based workflows to eliminate configuration drift.
- Optimize capacity, resilience, and cost; automate backups, DR, and security baselines.
- Identity, Security & Compliance: Integrate Keycloak (OIDC/SAML) with apps and services; automate client/realm config and secret lifecycles.
- Shift-left security with SAST/SCA/secret scanning, container image scanning, and signed SBOMs embedded in CI/CD.
- Observability & SDLC Operational Excellence: Standardize telemetry (metrics, logs, traces), define SLOs/SLIs, automate alerting, and codify incident response and postmortems.
- Automate environment resets, data refreshes, smoke tests, release readiness, and config promotion.
- Data, Analytics & AI Alignment: Orchestrate and integrate with data pipelines so applications, data transformations, and analytics refreshes release coherently. Partner with data engineering to automate pipeline deployments (batch/near-real-time), schema migration flows, and secure data access to RDS (Postgres/MySQL) and S3. Coordinate Tableau Cloud extract/refresh automation as part of release trains. Integrated repositories: define versioning and promotion standards for code, infrastructure, data schemas, and ML assets (e.g., model artifacts), ensuring traceability from commit → build → deploy → MLOps & AI Engineering: Work with AI/ML teams to productionize models with CI/CD for training/packaging/serving, model registry and approval workflows, and safe rollout/rollback of model versions. Enable feature/config management, secrets/IAM for data and model services, and integrate model-specific monitoring (data quality, drift, performance). Support serving patterns that embed models into microservices or batch scoring jobs on AWS (tooling such as MLflow/SageMaker or equivalents, as appropriate). QA Automation Engineering Alignment: Partner closely with QA Automation Engineering to integrate automated UI, API, and end-to-end test suites into CI/CD, ensuring consistent gating, fast feedback loops, and reduced reliance on manual validation. You'll contribute to test environment reliability, improve test data automation, and ensure QA automation becomes a first-class, scalable component of the delivery pipeline.
Requirements
- Proven track record turning manual or semi-automated delivery into fully automated pipelines that lift throughput and reliability.
- Deep Jenkins experience (declarative pipelines, shared libs, multi-stage) and Nexus artifact governance; strong Git workflows and release orchestration.
- Hands-on with AWS (EC2, ECS, EKS, ELB, S3, RDS, IAM) and networking; skilled with Terraform (preferred) or CloudFormation; container best practices (multi-stage Dockerfiles, image hardening, RBAC, ingress/autoscaling).
- Comfortable embedding automated test suites (Java, JS/TS, Python) as pipeline gates; experience with security scanning and SBOMs; strong telemetry and actionable alerting.
- Experience partnering with data/analytics teams to automate data pipelines and integrate data refreshes into application releases.
- Familiarity with MLOps concepts: model packaging, registries, approval workflows, automated promotion, monitoring for drift and data quality, and secure model serving.
- Practical knowledge of Postgres/MySQL operations and secure data access on AWS; awareness of Tableau Cloud deployment/refresh patterns.
- Bias to automate and remove toil; pragmatic, security-first, and documentation-driven. Excellent partner to engineering teams; strong communication and enablement skills. A strong communicator who can partner with developers, QA & Engineering teams. You provide clarity, documentation, and guidance while driving engineering excellence across the ecosystem.
Benefits
- Competitive compensation
- Flexible work schedule
- Remote or in-office work
- Personalized benefits program
- $1,500 for professional training and classes
- Free English or French tutoring classes
- Free gym access
- Free coffee & snacks
- Regular events & team building activities
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