What This Role Actually Is

It is a specialized FinOps and Azure infrastructure optimization role focused on identifying cost inefficiencies and landing measurable savings across high‑impact Azure services.

The team is specifically targeting 5× savings in Cosmos DB and meaningful reductions across compute, Redis, storage, event streaming, and Postgres.

Core Responsibilities

1. Azure Cost & Utilization Analysis

- Analyze spend patterns using Azure Advisor and Azure Cost Management + Billing .
- Identify top cost drivers, inefficiencies, and waste.
- Build clear baseline → root cause → recommendations → savings forecast reports.

2. Optimize High‑Impact Azure Services (Primary Focus Areas) You will work hands‑on to tune and rightsize:

Cosmos DB

- – RU/s optimization
- – Indexing & partitioning strategy
- – Autoscale vs. manual throughput
- – TTL, point‑read usage, query efficiency
- – Target: up to 5× cost reduction

Compute (VMs / VMSS / AKS)

- – Right‑sizing vCPU/RAM
- – Node pool strategy
- – Limits/requests cleanup
- – HPA/VPA evaluation
- – Reservations, Spot, Savings Plans

Azure Cache for Redis

- – SKU sizing, eviction policies, memory pressure tuning

Storage (Blobs, Files)

- – Tiering, lifecycle management, retention optimization

Event Hubs

- – Throughput units, consumer efficiency, capture strategy

Azure Database for Postgres

- – Instance sizing, query tuning, autovacuum/I/O alignment

These represent the largest and most addressable cost categories. 3. Microservices & PaaS Footprint Review

- Evaluate microservices for idle workloads, over‑provisioned instances, unnecessary persistence layers, excessive replicas.
- Identify opportunities to consolidate or scale down.

4. Capacity Planning & Scaling with Engineering Leads

- Work with leads to define realistic SLO‑aligned capacity baselines .
- Optimize autoscaling triggers and eliminate chronic over‑allocation.
- Ensure sustainable long‑term cost governance.

5.



Deliver Transparent, Actionable Recommendations Your output is not academic analysis —it must be:

- Practical
- Quantified
- Prioritized by impact
- Low‑risk to implement

Examples:

- Rightsize VMSS SKU
- Reduce RU/s on least‑used partitions
- Fix Redis memory pressure
- Adjust node pool strategy
- Introduce storage lifecycle policies
- Optimize Postgres IOPS vs. workload

6. Operate Independently After Onboarding

- Own the full investigation → diagnosis → recommendation → validation pipeline.
- Communicate findings clearly to senior technical and non‑technical stakeholders.

Must‑Have Skills (Top 3) Azure Infrastructure Cost Optimization & FinOps expertise

1. Strong with Azure Advisor, Cost Management + Billing, reservations, tagging, anomaly detection, dashboards.

Hands‑on optimization experience with Cosmos DB, Compute (VMs/VMSS/AKS), Redis, Storage, Event Hubs, and Azure Postgres

1. Ability to materially reduce spend across these services.

Infrastructure performance analysis & capacity/utilization engineering

1. Deep understanding of CPU/memory behavior, microservice patterns, and scaling mechanisms.

Required Experience

- 5+ years with Azure infrastructure at scale.
- Strong understanding of AKS, VMSS, microservices resource behavior.
- Proven track record of measurable cost savings in large Azure environments.
- Ability to translate complex technical findings into clear action plans.
- Excellent stakeholder communication skills.

Nice to Have

- Terraform / Bicep experience.
- Observability stack knowledge: Azure Monitor, Log Analytics, App Insights.
- JVM/container tuning background for services running on AKS or VMSS.
- Experience implementing FinOps governance practices.

Success Metrics

- Cosmos DB spend reduced by up to 5× without performance regression.
- Compute savings of 30–50% through rightsizing and scale adjustments.
- Storage & data savings of ~25% through lifecycle and tiering.
- Improved governance (tag coverage, budgets, alerting).

Thank you!

📌 Cloud Cost Optimization Engineer (Vancouver)
🏢 IFG - International Financial Group
📍 Vancouver