DevOps EngineerJourney Capital • Montreal (administrative region), QC, CA

DevOps Engineer

Journey Capital • Montreal (administrative region), QC, CA

Il y a 1 jour

Type de contrat

Temps plein

Description de poste

Overview

The career you’ve always wanted starts here. This is your chance to work in a place that is making a positive difference for SMBs across Canada. Where teamwork, flexibility, and professional growth are encouraged every step of the way. Ready to take your career to a whole new level? Journey Capital is here to get you there. Not your average fintech company.

As Canada’s leading online lender, Journey Capital is dedicated to helping clients with a collaborative, adaptive, and customer-centric approach. We are setting new benchmarks in the industry by embracing innovation, transparency, and ethical lending standards.

About The Opportunity

We are building the future of online lending. Our technology is a mix of building world-class user experiences for our partners and direct customers, automating workflows to enable fast lending decisions, and generating precise money movements and calculations to service our customers. We emphasize scalability, security, reliability and accuracy.

You’ll be the backbone of our delivery platform, designing, building, and operating CI / CD, cloud infrastructure, identity, and reliability practices that power a microservices ecosystem across Java, JS / TS, Python services, Salesforce, among others. Near‑term, your priority is to convert semi‑automated and manual processes into fully automated workflows that increase deployment frequency, reduce lead time for changes, and raise engineering productivity. You’ll also align platform automation with our data, analytics, and AI strategy so applications and data products ship together, safely and fast.

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.

What you’re bringing to the table

Alongside Unwavering Ethical Principles, You Showcase

Automation‑First Delivery Expertise

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.

Cloud, Containers & IaC

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).

Quality, Security & Observability

Comfortable embedding automated test suites (Java, JS / TS, Python) as pipeline gates; experience with security scanning and SBOMs; strong telemetry and actionable alerting.

Data, Analytics & AI Collaboration

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.

Versioning disciplines for integrated repositories (code, infra, schemas, and model artifacts) with clear branching and promotion standards.

Practical knowledge of Postgres / MySQL operations and secure data access on AWS; awareness of Tableau Cloud deployment / refresh patterns.

Mindset & Collaboration

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.

The Perks

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

Empowering Canadian entrepreneurs

We deliver a seamless remote experience that gives our clients the peace of mind to move their business forward. Our aim is to equip underserved Canadian entrepreneurs with the right credit, tools and experience to help them reach their financial objectives fast.

Sound like something you’d be interested in? Let’s talk.

Journey Capital

Here to get you there.

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