Sr. FinOps Cloud Engineer

Meet the Moment with Alteryx

We're living through a once-in-a-generation shift in how work gets done. Data, automation, and AI are quickly becoming the center of every business decision - and Alteryx is leading the transformation.

You'll be working on the challenges that sit at the heart of modern business. No matter your role, the work you do will help organizations move faster, see more clearly, and tackle questions that used to feel impossible.

If you're ready to meet the moment with innovation, curiosity, and excellence, there's a place for you here.

We are looking for problem solvers, innovators, and analytical thinkers who challenge the status quo. If you are an experienced technologist passionate about the intersection of cloud architecture, big data, machine learning workloads, and financial accountability, this role is for you.

As a Senior FinOps Engineer, you will serve as the technical backbone and subject matter expert for cloud financial operations across our global engineering organization. This role bridges deep cloud infrastructure mechanics with data engineering, algorithm design, and business economics. You will architect automated reporting pipelines, develop unit-cost metrics, govern procurement and operational policies, introduce FinOps practices for AI workloads, and partner closely with engineering squads, platform teams, and finance leaders to foster a culture of cost-aware engineering.

• Manage, curate, and normalize end-to-end cloud cost and usage datasets, ensuring high data fidelity, consistency, and standardized governance across multi-cloud environments.
• Define, build, and maintain automated cost, usage, and efficiency dashboards using Apache Superset, supported by SQL and data extraction pipelines.
• Design and deploy automated anomaly detection algorithms, statistical models, and alerting mechanisms to detect spending spikes, runaway workloads, and unexpected cost regressions in near real time.
• Benchmark, track, and report on cloud consumption, forecast variance, unit economics, and realized savings to engineering teams and leadership.
• Implement and refine tagging governance, business cost-allocation models, and unit economics metrics, such as cost per customer, cost per query, or cost per pipeline run.

• Own and optimize cloud financial management platforms for reporting, cost optimization, and performance measurement. Our environment includes Cloudability, PointFive, ProsperOps, and Larridin; experience with comparable platforms is welcome.
• Design, build, and maintain automation workflows and scripts to identify and reclaim idle, underutilized, or orphaned resources, including compute instances, unattached volumes/IPs, outdated snapshots, and development/test environments.
• Lead enterprise-wide commitment strategies across AWS, Azure, and GCP, managing portfolio coverage, risk, and utilization for Reserved Instances, Savings Plans, and applicable provider-specific commitments.
• Partner with software, platform, and SRE teams to analyze utilization telemetry, implement rightsizing recommendations, and optimize compute and storage resources.

• Introduce and establish FinOps frameworks tailored to AI, ML training pipelines, and LLM inference workloads.
• Establish Total Cost of Ownership (TCO) and Return on Investment (ROI) models for AI infrastructure, including GPU clusters, vector databases, model hosting endpoints, and third-party AI APIs.
• Collaborate with AI/ML engineering teams to evaluate model inference performance against operational costs, improving token efficiency and hardware utilization.

• Establish and enforce cloud cost and operational policies across accounts, subscriptions, regions, and resource configurations.
• Participate in architectural design and cloud capacity planning for new projects, services, and major infrastructure changes.
• Oversee third-party cloud marketplace software procurement, ensuring spending aligns with enterprise budgets and cloud discount commitments.
• Review production release schedules from a cost-impact perspective, incorporating pre-production load-testing analysis and cost guardrails.
• Partner with Financial Planning & Analysis (FP&A) and engineering leaders to track monthly variance, improve forecasting models, and translate technical decisions into business impact.
• Collaborate with engineering, platform, and finance teams across India and the United States. Lead knowledge-sharing sessions, develop technical documentation, and promote FinOps best practices across engineering teams.

• 5+ years of hands-on experience in cloud engineering, DevOps, SRE, or cloud financial management, with strong expertise in AWS and/or Google Cloud and familiarity with Azure.
• Proven experience applying FinOps principles (Inform, Optimize, Operate) in a modern cloud-native enterprise environment.
• Advanced SQL skills and experience building automated data workflows, metrics engines, and dashboards using BI tools such as Apache Superset.
• Experience creating or configuring automated alerting rules, statistical anomaly detection, or threshold-based algorithms for infrastructure telemetry.
• Direct experience managing cloud commitment portfolios, including Savings Plans and Reserved Instances, and optimizing effective savings rates.
• Strong scripting or coding skills in Python, Bash, or Go to build automated resource reclamation, API integrations, and policy enforcement tools.
• Strong communication skills and demonstrated ability to contribute to architectural planning, implement governance policies, and explain trade-offs between cost, performance, reliability, and delivery speed.

• FinOps Certified Practitioner or FinOps Certified Professional certification.
• Cloud Architect or SysOps certifications (AWS, Azure, or GCP).
• Experience implementing FinOps practices for AI/ML workloads and GPU compute environments, including TCO/ROI analysis for LLMs and distributed training.
• Experience with cloud marketplace procurement workflows and private offer agreements.
• Experience with container cost allocation across Kubernetes, EKS, GKE, or AKS using tools such as Kubecost or OpenCost.
• Working knowledge of the FinOps Open Cost and Usage Specification (FOCUS), including its schema and taxonomy standards.

• Complete an assessment of existing multi-cloud accounts, commitment coverage portfolios, and FinOps tooling.
• Establish baseline dashboards for core services, identify idle-resource optimization opportunities, and improve commitment coverage.
• Participate in cloud architectural reviews and establish partnerships with AI/ML and platform engineering teams.

• Deploy automated anomaly detection and idle-resource cleanup solutions into production workflows.
• Establish FinOps practices for AI workloads, providing TCO and ROI visibility into AI infrastructure and model inference.
• Formalize cloud marketplace procurement governance and cost reviews within operational release processes.
• Standardize multi-cloud cost allocation models and deliver trusted unit-cost KPIs across product lines.

• Build a proactive engineering culture where financial efficiency is incorporated into architecture and infrastructure decisions.
• Maintain scalable, automated cloud cost management and optimization capabilities that evolve with business and technology needs.

As Alteryx continues to scale its platform and invest in AI capabilities, managing cloud infrastructure efficiently is essential to sustainable growth.

In this role, you will go beyond monitoring cloud costs to build automation, improve financial visibility, influence architectural decisions, and establish meaningful metrics that connect engineering investments with business value.

Your work will directly contribute to making our cloud infrastructure more efficient, scalable, and financially sustainable.

Find yourself checking a lot of these boxes but doubting whether you should apply? At Alteryx, we support a growth mindset for our associates through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences.

This position involves access to software/technology that is subject to U.S. export controls. Any job offer made will be contingent upon the applicant’s capacity to serve in compliance with U.S. export controls.