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

Analyze spend patterns using Azure Advisor and Azure Cost Management + Billing .

Identify top cost drivers, inefficiencies, and waste.

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

RU/s optimization

Indexing & partitioning strategy

Autoscale vs. manual throughput

Compute (VMs / VMSS / AKS)

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

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.

5. Deliver Explicit, Actionable Recommendations




Your output is not academic analysis —it must be:

Practical

Quantified

Prioritized by impact

Low‑risk to implement

Examples:

Reduce RU/s on least‑used partitions

Fix Redis memory pressure

Adjust node pool strategy

6. Operate Independently After Onboarding

Communicate findings clearly to senior technical and non‑technical stakeholders.

Must‑Have Skills (Top 3)

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

Ability to materially reduce spend across these services.

Infrastructure performance analysis & capacity/utilization engineering

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.

Nice to Have

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).

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