Cloud Efficiency Engineer (AWS/FinOps)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cloud Efficiency Engineer (AWS/FinOps) based in Australia.

As a Cloud Efficiency Engineer, you’ll own cloud efficiency end to end, turning infrastructure and operational costs into actionable engineering decisions. You’ll trace AWS and observability costs down to the technical drivers behind them, build detailed cost models, and identify opportunities to improve margins. This is a hands-on engineering role where you’ll implement optimisations, partner with engineering teams, and measure the real-world impact of every change. You’ll work closely with engineering leadership, platform teams, data specialists, and Finance to connect technical decisions with business outcomes. The role requires balancing cost reduction with reliability, throughput, and customer experience. You’ll have significant autonomy and the opportunity to directly influence growth through technical efficiency in a large-scale, remote-first SaaS environment.

Accountabilities

• Trace cloud cost signals to their underlying technical causes, including customer-level job costs, state-machine changes, GraphQL costs by function, and per-operation unit economics.
• Build and maintain detailed cost models for common and high-cost operations, enabling the organisation to understand how changes in traffic and usage affect margins.
• Analyse cost trends, identify optimisation opportunities, and prioritise initiatives based on expected savings, risk, effort, and required stakeholder involvement.
• Implement safe, measurable AWS and infrastructure optimisations directly where changes fall within your area of ownership.
• Partner with engineering teams responsible for affected systems to drive larger optimisation initiatives using evidence-based recommendations and measurable outcomes.
• Lead efficiency improvements across Datadog and observability tooling alongside AWS, identifying opportunities to reduce monitoring and telemetry costs without compromising visibility.
• Establish credible cost baselines before optimisation initiatives and verify realised savings in production after changes are implemented.
• Build guardrails, attribution mechanisms, alerting, and cost-visibility tooling to identify regressions early and prevent unexpected cost increases.
• Translate effectively between engineering and Finance, turning financial questions into technical analysis and engineering changes into clear financial outcomes.
• Present cost models, optimisation opportunities, trade-offs, and verified results with confidence to technical and executive stakeholders.
• Maintain a strong focus on ensuring cost optimisation does not negatively affect system reliability, performance, throughput, or customer experience.
• Use AI tools and techniques to accelerate analysis, modelling, problem solving, and engineering execution while validating outputs rigorously.

Requirements:

• Proven experience delivering meaningful, measurable AWS cost savings in a scaled production environment, with the ability to explain the baseline, diagnosis, solution, trade-offs, and verified outcome.
• Strong hands-on engineering background, including the ability to read code, write code, troubleshoot systems, and implement production changes rather than simply producing recommendations.
• Strong systems-diagnosis and analytical skills, with the ability to investigate ambiguous cost signals and identify precise technical causes.
• Solid understanding of AWS infrastructure, cloud economics, production systems, and the relationship between technical architecture and operational costs.
• Strong commercial and technical judgement, including the ability to distinguish worthwhile savings opportunities from changes that introduce unacceptable reliability or customer-experience risks.
• Demonstrated ability to influence and collaborate with engineering teams outside your direct reporting line to deliver cross-functional technical improvements.
• Strong numerical and analytical discipline, with the ability to develop defensible methodologies and stand behind cost calculations and savings claims.
• Experience with Datadog or observability cost optimisation is highly desirable.
• FinOps engineering experience or experience partnering with Finance on unit economics, cost attribution, or financial modelling is advantageous.
• Experience building granular cost attribution systems, automated cost guardrails, or cost-visibility tooling is a plus.
• Experience with GraphQL at scale, developer tooling, CI/CD, cloud infrastructure, SaaS platforms, or observability products is beneficial.
• Experience working in a scaled SaaS, platform, or technology environment with a significant AWS footprint is advantageous.
• A finance, commercial, or business background alongside strong engineering experience would be valuable.
• Strong communication and stakeholder-management skills, with the ability to translate complex technical and financial concepts for different audiences.
• A proactive, curious, autonomous mindset and willingness to take ownership of ambiguous, high-impact problems.
• Full-time availability within the ANZ or PST time zones and appropriate work rights for the relevant region.

Benefits:

• 100% remote working , with the flexibility to work from anywhere in the world for up to 6 weeks per year , in addition to the fully remote setup.
• 20 days of paid annual leave plus 10 days of sick and carer’s leave .
• 16 weeks of paid parental leave for primary carers and 6 weeks for secondary carers .
• Remote-work allowance to support home-office equipment, coworking spaces, or alternative working arrangements.
• Confidential Employee Assistance Program (EAP) and mental health support.
• Dedicated time and budget for professional learning, conferences, courses, coaching, and skills development.
• Retirement and health coverage, with specific benefits depending on location.
• Opportunity to work on high-impact cloud efficiency and FinOps challenges with direct influence on technical and business performance.
• Significant autonomy and ownership within a fully distributed engineering environment.
• Exposure to AWS, Datadog, cost attribution, cloud economics, infrastructure optimisation, and AI-assisted engineering.
• Collaborative culture focused on inclusion, diverse perspectives, continuous learning, and high-quality engineering.
• Benefits may vary slightly by country and will be confirmed based on your location.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.