Your Mission
The Product Developer builds reusable, robust components—data models, analytics, apps, and orchestrations—that power Process Intelligence outcomes at scale. They turn business logic into production-grade software with clean interfaces, observability, and performance.
How Phase I Prepares You for the Product Developer Role
Phase I builds the technical, analytical, and architectural foundations required to develop scalable process intelligence products.
Understand how process data is structured, modeled, and translated into analytical logic.
Build analytical applications, reusable tools, and automated solutions on top of process intelligence.
Design products that scale across users, processes, and organizational boundaries.
Phase I ensures Product Developers build solutions that are not only functional, but scalable and reusable.
What Great Product Developers Do
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Turn KPI logic and RCA trees into clean data models and services.
Design UX that guides decisions (KPI → insight → action).
Bake in observability (quality checks, lineage, telemetry).
Optimize performance and cost; engineer for reuse and maintainability.
Collaborate tightly with Solution/VE to shorten idea→prod cycle.
Core Responsibilities
Modeling & pipelines — event logs, transforms, tests, freshness SLAs.
Analytics & apps — dashboards, decision UIs, automation triggers.
Quality & reliability — validation, CI/CD, error budgets, rollbacks.
Security & compliance — data contracts, access, audit.
Documentation & reuse — components, patterns, developer guides.
Process Intelligence Expertise
The technical foundation that powers scalable solutions
Data Foundation
Event data (case/activity/attributes), conformance, variants.
KPI math (cycle time, throughput, DSO, touchless rate).
Automation & orchestration (NBAs, queues, approvals, SLAs).
Enterprise Integration
Enterprise systems (ERP, SCM, CRM) and integration patterns.
Performance & Scale
Perf/scale (partitioning, caching, incremental compute).
Outcomes & Success Metrics
Reliability (SLA/SLO adherence, error rate, MTTR).
Performance (query latency, pipeline freshness).
Adoption & coverage (active users, feature usage).
Reusability (component reuse, duplicate logic reduced).
Delivery speed (lead time, cycle time to production).
A Day in the Life
Backlog grooming and tech design review.
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Who You Work With
Your collaboration network spans the entire organization
Solution Partner, Value Engineer, Platform/Data.
CoE developers, security/compliance, process SMEs.
SIs for joint build or scale-out.
Required Skills
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