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Salary
≈ $16k – $32k per year (Estimated)
Location
In office (Pune)
Seniority
Middle · 3+ years exp

First seen by Alion on Oct 1, 2026.

Overview
Company
Impact
Profile match
ZOOP is an IT and Services company that provides a digital ID verification platform, with AI-based user authentication, address verification, financial analysis and digital contracting.

We're looking for a FinOps Engineer with a DevOps backbone who has an almost obsessive eye for cost leaks, idle resources, and inefficiencies across our platform. If unused EBS volumes, oversized instances, or a forgotten dev environment running on weekends genuinely bother you, you'll fit right in. This isn't a passive reporting role. You'll be expected to proactively hunt for waste, propose optimisations, and drive strategic cost conversations with engineering, SRE, and leadership across ZOOP's entire platform from infrastructure and Kubernetes clusters to data pipelines and third-party services.

Responsibilities:

  • Continuously audit ZOOP's cloud footprint (AWS/Azure/GCP) end-to-end compute, storage, networking, databases, observability stack, and SaaS tooling and flag every form of waste, big or small.
  • Proactively propose cost-reduction strategies rather than waiting to be asked; bring data, options, trade-offs, and a recommendation to the table.
  • Lead monthly/quarterly cost reviews with engineering and product leadership; turn billing data into actionable conversations.
  • Build cost visibility dashboards and chargeback/showback models so every team at ZOOP knows what they're spending and why.
  • Drive rightsizing, autoscaling tuning, Spot/Reserved Instance/Savings Plan strategies, and storage tiering across the platform.
  • Embed cost guardrails into CI/CD pipelines, IaC (Terraform/CloudFormation), and Kubernetes manifests to catch wasteful resources before they're deployed.
  • Optimise Kubernetes cost efficiency using tools like Kubecost, OpenCost, or Karpenter; tune requests/limits, HPA/VPA, and node pools.
  • Set up automated alerts and anomaly detection for budget breaches, idle resources, and runaway costs.
  • Partner with Finance for forecasting, unit economics (cost per user/transaction), and cloud budget planning.
  • Evangelise a cost-aware engineering culture, run internal sessions, write playbooks, and make FinOps a shared responsibility, not a finance afterthought.

Requirements:

  • Someone with genuine OCD around cost and wastage; you can't sleep knowing a non-prod cluster ran all weekend at full capacity.
  • A DevOps practitioner first, who understands why costs happen at the infrastructure level, not just someone reading billing reports.
  • Naturally proactive; you don't wait for tickets; you spot patterns, dig in, and propose changes before anyone asks.
  • Comfortable challenging engineering decisions diplomatically when they're expensive, and equally comfortable defending necessary spend to finance.
  • A clear communicator who can talk to both a senior engineer about Karpenter configs and a CFO about quarterly burn.
  • 3+ years of hands-on experience in DevOps, Cloud Engineering, SRE, or Cloud FinOps roles.
  • Strong working knowledge of at least one major cloud provider (AWS preferred), including native cost tools (Cost Explorer, CUR, Azure Cost Management, or GCP Billing).
  • Proficiency with Infrastructure as Code (Terraform, CloudFormation, or Pulumi).
  • Hands-on experience with Docker and Kubernetes (EKS/AKS/GKE).
  • Scripting in Python, Bash, or Go for automation, reporting, and cost tooling.
  • Familiarity with CI/CD tools (Jenkins, GitLab CI, GitHub Actions, ArgoCD).
  • Solid grasp of cloud pricing models: On-Demand, Reserved Instances, Savings Plans, Spot/Preemptible, committed-use discounts.
  • SQL skills for querying billing data (AWS CUR via Athena/Redshift, BigQuery billing exports).

Nice to Have:

  • FinOps Certified Practitioner (FOCP) certification.
  • Cloud certifications (AWS, Azure, or GCP).
  • Experience with FinOps platforms (CloudHealth, Cloudability/Apptio, Spot.io, Vantage, Kubecost).
  • Exposure to multi-cloud or hybrid-cloud cost optimisation.
  • Understanding of SaaS unit economics (cost per customer, cost per transaction, gross margin impact).
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