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Open nowPosted 36 hours ago

(529591395575)-GFT_OUT: FinOps Cloud Engineer dla HSBC

RITS129 open roles

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. RITS postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 36 hours ago

RITS median: 1 days open

The posting

As the FinOps Cloud Engineer (FinOps Optimisation Specialist), you’ll work hands-on across Azure, AWS, and GCP to identify, quantify, and deliver cloud cost optimisation opportunities—initially with a focus on logging/observability and storage cost drivers. You’ll combine strong engineering capability (automation, IaC, scripting) with FinOps practice (allocation, governance, savings forecasting) to design and implement sustainable controls that reduce run-rate, improve transparency, and prevent cost re-growth. You’ll partner closely with cloud platform engineering, SRE/observability, security, and product/application teams to analyse usage patterns, propose improvements, secure governance approvals, and implement changes safely in line with client risk, compliance, and change controls. Success in the role means measurable savings delivered at pace, with clear reporting, repeatable automation, and improved cost-aware engineering behaviours across the multi-cloud estate.

Location: Krakow (the team works in the office 6x a month)

Rate: up to 145 PLN/h net + VAT (B2B)

Optimisation delivery:

• Identify opportunities across ingestion, retention, tiering, sampling, routing, and exclusion rules; prioritise by ROI and risk.

• Implement changes via automation/IaC with rollback plans and post-change validation.

• Build and deploy automation for logging and storage cost optimisation across a multi-cloud estate at enterprise scale.

• Access and analyse logging data directly using cloud native tooling to identify cost drivers and reduction opportunities.

• Produce optimisation proposals with projected saving forecasts.

• Operate within client governance and compliance standards, obtaining appropriate approvals before implementing changes.

FinOps governance:

• Support tagging/labels and allocation model improvements for chargeback/showback accuracy.

• Define and maintain policies/guardrails (e.g., default retention standards, workspace quotas, budget alerts).

Stakeholder management:

• Run optimisation “clinics” with platform/app teams; agree actions, owners, timelines, and expected savings.

• Produce executive-ready reporting for senior stakeholders (trend, forecast vs actual, risks).

• Present technical findings and recommendations to cloud platform leads and senior engineering stakeholders.

Operational excellence:

• Create runbooks, controls, and documentation; ensure changes pass risk/compliance checks.

• Monitor for cost regression and create automated “drift” detection

• Strong working knowledge of Azure (core services, identity, networking, governance) and good knowledge of AWS and GCP cost drivers and pricing mechanics:

• Azure: Log Analytics / Azure Monitor, Diagnostic Settings, Storage Accounts, Event Hub, Sentinel, Azure Policy, Cost Management.

• AWS: CloudWatch Logs, S3 lifecycle, Cost Explorer/CUR.

• GCP: Cloud Logging, Log Router/Sinks, BigQuery, Storage lifecycle policies, Billing exports.

• IaC/automation: Terraform, CI/CD (GitHub Actions/Azure DevOps), policy-as-code.

• Practical understanding of FinOps principles, including cost allocation, showback/chargeback concepts, optimisation levers, and cost governance.

• Understanding of cloud governance/compliance approaches and how to implement guardrails in enterprise environments.

• Hands-on experience with at least two public cloud platforms (AWS, Azure, and/or GCP), including their native logging and monitoring services.

• Strong understanding of logging/observability architecture, including log ingestion and routing, retention policies, and storage cost drivers.

• Proven ability to analyse logging data at scale to identify cost drivers and deliver measurable cost reduction opportunities.

• Demonstrated experience building and deploying automation at scale using Python, Bash, and/or Terraform (including CI/CD and repeatable deployment patterns where applicable).

• Experience producing savings forecasts, building business cases, and writing structured optimisation proposals with clear assumptions and impacts.

• Strong communication skills, with experience presenting technical analysis and recommendations to senior technical stakeholders and influencing outcomes.

• Experience working in a highly governed enterprise environment, operating within compliance, operational risk, and change control frameworks.

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