Our team is building a next-generation Cloud Demand Forecasting Tool to replace legacy spreadsheet-driven processes and fragmented portals used to plan infrastructure capacity across Baremetal & 3PC services. This is a greenfield modernization effort, you will architect and build a scalable, maintainable platform that enables 500+ concurrent users across dozens of lines of business to submit, approve, aggregate, and actualize infrastructure demand forecasts on a rolling horizon. You will own the migration from legacy tooling and deliver a system that reduces manual coordination effort by 80%, accelerates planning cycles from weeks to days, and achieves greater than 90% forecast accuracy within a specified window.
Design and build the end-to-end platform: web portal, RESTful APIs, CLI, and data pipelines for cloud infrastructure demand forecasting and lifecycle management.
Implement complex, configurable workflow engines supporting a multi-stage demand forecast lifecycle with SLA tracking, automated routing, and notification triggers.
Build a demand normalization and validation layer that standardizes hardware SKUs, translates bare metal demand into sellable/vendable units, and validates submissions against real-time constraints (data center power/space, budget, lead times).
Develop hierarchical forecast aggregation across business units, geographies, resource types, time horizons, and scenario types (baseline, stretch, low-case).
Create executive dashboards and reporting modules with drill-down capabilities, variance tracking (forecast vs. actual), exception queue management, and multi-format output (CSV, JSON, Excel, API).
Implement predictive analytics capabilities: time series analysis, seasonal decomposition, ML-based demand prediction, and confidence interval quantification.
Architect for scale and reliability.
Own security and access control: SSO integration, granular RBAC, encryption at rest and in transit, complete audit logging with observability integration.
Required Qualifications
7+ years of software engineering experience, with at least 3 years building enterprise-grade internal tools or planning/forecasting platforms.
Strong experience migrating from legacy systems (spreadsheets, fragmented portals) to modern, consolidated web applications.
Deep expertise in full-stack development, building both the backend services and frontend interfaces end-to-end.
Proven track record designing and implementing complex stateful workflow engines with multi-level approval chains, configurable routing, and SLA enforcement.
Experience building RESTful APIs with versioning, rate limiting, comprehensive error handling, and interactive documentation (OpenAPI/Swagger).
Strong data engineering skills: ETL pipelines, data normalization, validation frameworks, and integration with data lakes.
Experience with role-based access control systems and enterprise SSO (SAML/OIDC).
Solid understanding of relational database design, query optimization, and data archival strategies.
Preferred Qualifications
Experience in infrastructure capacity planning, cloud resource management, or supply chain forecasting domains.
Familiarity with predictive analytics, time series forecasting, seasonal decomposition, scikit-learn or equivalent ML frameworks.
Experience building CLI tools that operate against platform APIs.
Background working with financial planning workflows, budget approval chains, or fiscal tracking systems.
Experience with observability and audit logging pipelines (Splunk, Grafana, or equivalent).
Knowledge of deep learning architectures for time series forecasting, particularly LSTM (Long Short-Term Memory) networks, transformer-based models (e.g., Temporal Fusion Transformers), or Prophet for demand prediction and seasonal pattern recognition at scale.
Frontend: React, TypeScript, modern component libraries; data visualization with D3.js/Recharts for interactive dashboards
Backend: Python (FastAPI/Django) with service-layer architecture for workflow orchestration, validation, and aggregation
APIs: RESTful services with OpenAPI/Swagger
CLI: Python (Click/Typer) or Go-based CLI for API interaction and workflow automation
Database & Storage: PostgreSQL for transactional/workflow data; integration with Data Lake.
Data Pipelines: Apache Airflow (or equivalent) for ETL, normalization, validation, and scheduled forecasting workflows
Analytics/ML: Python (pandas, scikit-learn, statsmodels) for time series forecasting, seasonal analysis, and demand modeling (MAPE-driven). Knowledge of advanced time series models like LTSM (Long Short-Term Memory) is a plus.
Security: SSO (SAML 2.0/OIDC), RBAC, TLS (in transit), AES-256 (at rest), and DLP controls
Messaging: Kafka (or equivalent) for event-driven workflows; notifications via Email, Slack, Unibox
Caching: Redis for sessions and frequently accessed data
Observability: Logging and monitoring via Splunk/Grafana, APM, SLA dashboards
Infrastructure: Kubernetes-based microservices, CI/CD pipelines, automated backups
File I/O: CSV, Excel (openpyxl/Apache POI), JSON for bulk import/export
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