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

Job title

DevOps Engineer

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

No Education Requirement

Location requirements

Report this job

See something inaccurate? Let us know and we'll update the listing.

Report job