Senior Data Analyst

Essential functions

• Build and maintain cloud cost attribution models that accurately allocate infrastructure spend (compute, accelerators, storage, networking, data transfer) across teams, products, and workloads, providing clear visibility into who is spending what and why.
• Build and maintain cost of revenue pipelines and models
• Partner with infrastructure, finance, and procurement stakeholders to analyze utilization patterns, identify inefficiencies, and drive optimization initiatives that improve the cost-effectiveness of our non-accelerator cloud resources.
• Develop forecasting models for non-accelerator infrastructure demand, incorporating business growth projections, product roadmaps, and historical spend trends to enable proactive capacity planning and budget accuracy.
• Define and track unit cost metrics (e.g., cost per request, cost per GB stored, cost per pipeline run) and identify opportunities to reduce them, influencing infrastructure and engineering roadmaps with data-driven recommendations.
• Develop unit cost economics for various workloads and applications, and using the metrics to drive efficiency efforts across product and infrastructure teams.
• Build a cost-aware culture across the organization by creating self-serve dashboards, automated reporting, and accessible datasets that give engineering and finance teams clear visibility into cloud spend and efficiency metrics.

Qualifications

• 6+ years of experience in data science, analytics, or FinOps roles, with a focus on cloud infrastructure cost analysis, capacity planning, or efficiency optimization.

• Experience building spend forecasting models and large-scale cost attribution systems.

• Deep knowledge of cloud billing systems, cost allocation methodologies, and spend optimization levers (e.g., reserved instances, committed use discounts, rightsizing, spot/preemptible usage).

• A passion for the company's mission of building helpful, honest, and harmless AI.

• Expertise in Python, SQL, forecasting, data modeling and data visualization tools.

• Experience in turning open questions and data into concise and insightful analysis.

• Highly effective written communication and presentation skills.

• Lead the design and implementation of systems that enable cloud and OnPrem capacity forecasting, including planning models to support application onboarding, expansion, and repatriation.

• Partner with application and infrastructure teams to analyze workload characteristics, optimize placement decisions, and reduce infrastructure waste through intelligent workload optimization strategies.

• Develop and support internal tools and APIs that provide real-time and forecasted capacity signals to hardware procurement, infrastructure owners, and finance partners.

• Design and build quota and subscription management solutions to enable fair, scalable consumption of shared infrastructure resources.

• Collaborate with Hardware Engineering to define data-driven signals that guide purchase decisions for greenfield and brownfield environments.

• Support the onboarding of service providers by developing capacity insights and demand management capabilities that align with platform growth expectations.

• Partner closely with Finance, Procurement, and Cloud FinOps teams to align capacity forecasts with spend and budget expectations.

• Collaborate cross-functionally to maintain a strong governance model for capacity consumption, allocation, and scaling practices.

• Share best practices across teams and mentor engineers on platform scalability, cost efficiency, and operational resilience.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

We offer

• Opportunity to work on cutting-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, vision, dental, etc.
• Corporate social events
• Professional development opportunities
• Well-equipped office

About us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.