ERP D2O Process Architect (f/m/x)
Enpal
| Company | Enpal |
| Category | Data & Analytics |
| Location | Berlin |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 16 Jul 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer ATS (ashby) |
Description
Our goal is to have a solar system on every roof, a storage unit in every house, and an electric car in every garage. Enpal makes this possible with an integrated total solution for decentralized energy—from solar systems and battery storage to wall boxes, smart meters, and heat pumps. At the heart of it all is our AI-powered platform Enpal.One http://Enpal.One+, which intelligently connects thousands of systems and efficiently optimizes electricity procurement and feed-in on the energy market.
Are you ready for solutions that are more than just a promise and bring real quality of life to thousands of households every day? What you create at Enpal will deliver clean electricity tomorrow and bring about lasting change in how we use energy.
WHAT YOU’LL DO
Enpal is building the next generation of its ERP landscape, moving from traditional D365 F&O workflows toward an AI-driven operating model where agents translate demand signals into purchase orders autonomously, without manual intervention. The vision: a Demand-to-Order process that executes itself, with humans focused on defining the rules, validating the output, and continuously raising the bar.
As ERP Process Architect D2O, you are the Business Intent Owner for the Demand-to-Order domain. You own the end-to-end process design for demand planning, pricing foundations, and order generation — and you define what AI agents in the D2O squad should do, what they should escalate, and what requires human approval. You work closely with Technology, Procurement, Sales, and Controlling, and sit at the center of Enpal's agentic transformation.
PROCESS OWNERSHIP & AGENTIC DESIGN
- Own the E2E D2O process design: demand forecasting, demand signal integration, pricing logic, price master data, discount structures, and order generation
- Define outcome-oriented business intents for AI agents operating in the D2O domain, specifying what agents should do, what they should escalate, and what requires human approval
- Drive alignment between demand signals and ERP order generation, ensuring demand plans translate into purchase orders in D365 F&O with minimal manual intervention
- Own pricing master data governance: ensure pricing structures, discount logic, and price lists are correctly maintained and consistently applied across all order types and markets
GAP ANALYSIS & INITIATIVE MANAGEMENT
- Identify process gaps, inefficiencies, and root causes across the D2O domain; translate findings into structured, prioritized ERP initiatives
- Write and own Business Requirements Documents for D2O initiatives, structured, evidence-based, and designed for clean-core D365 implementation
- Monitor KPIs and proactively identify performance deviations in forecast accuracy, demand plan adherence, and pricing accuracy
- Act as process SME in cross-functional projects, system changes, and new business line onboarding
STANDARDS & GOVERNANCE
- Document and maintain process standards, ERP configuration guidelines, and operating procedures for the D2O domain
- Validate agent output against business intent: ensure agents are executing correctly and escalate when confidence thresholds are not met
- Represent D2O in ERP governance forums, design authority reviews, and cross-functional steering
WHAT YOU’LL BRING
- Proven experience as a Process Architect, Business Analyst, or similar role owning E2E process design in an ERP environment
- Strong expertise in Demand-to-Order processes: demand planning, pricing logic, discount structures, and order generation
- Hands-on experience with D365 F&O (or a comparable ERP system), ideally across Sales & Marketing, Procurement & Sourcing, and Master Planning modules
- Ability to write structured Business Requirements Documents and translate business complexity into clean process design
- Experience monitoring process KPIs and driving continuous improvement
- Openness to working in an AI-native delivery m