R&D Product Owner - Data, Analytics, Digital & AI Delivery (Pharma Industry) (WFH)

About the job:

Company Description

ERP Logic is a globally recognized SAP Cloud Solutions company, specializing in SAP implementation and application services. Since its inception in 2009, the company has grown significantly to over 1,000 employees and expanded its presence across the United States, Europe, the Middle East, India, and Israel. As one of the top three SAP reseller partners globally for SAP S/4HANA Grow and SAP S/4HANA Rise, ERP Logic serves over 500 customers, including both large enterprises and mid-sized companies. With deep expertise in SAP S/4HANA and SAP ECC, ERP Logic supports businesses in transitioning to advanced ERP systems with a customer-centric approach and sustainable solutions.

Role Description

The DADAI ( Data, Analytics, Digital & AI Delivery ) Domain Product Owner is accountable for translating approved product priorities into delivery-ready scope and for maximizing execution quality across products. The Product Owner owns the product backlog, clarifies requirements, defines acceptance criteria, and ensures delivery teams can execute with clear priorities, technical alignment, and quality standards.

The Product Owner acts as the primary delivery-facing interface between the domain Business Unit priorities (via the IT SHM / Product Manager) and the DADAI delivery factory / CoEs at the product level, ensuring continuous alignment between business intent, delivery execution, and backlog refinement.

Key Responsibilities

The Product Owner contributes execution input required for delivery planning, including:

Translating approved business priorities into clear product scope, epics, features, and user stories.

Identifying execution implications and collaborating with CoEs, Architecture, Data, and delivery teams to refine delivery-ready scope

Assessing execution dependencies, technical constraints, regulatory considerations, and data readiness implications at product level

Defining clear feature scope, acceptance criteria, assumptions, and delivery readiness inputs for planning

Ensuring backlog items are complete, clear, and meet DADAI quality standards prior to PI / sprint planning and delivery execution

Acting as the primary delivery-facing product authority for feature scope, backlog priorities, and acceptance decisions for ARTs, PODs, and vendor teams

Supporting operational feedback loops by translating production learnings, defects, and enhancement requests into backlog refinement and prioritized delivery actions

Success Measures:

Delivery Readiness & Planning Quality

Percentage of features entering PI / sprint planning with clear scope, acceptance criteria, dependencies, and required architectural or data inputs identified.

Minimizing late discovery of dependencies, data readiness gaps, or scope ambiguity during planning and execution.

Execution Quality

Plan adherence of sprint / PI predictability for committed feature delivery.

Percentage of accepted stories / features meeting definition of done without major rework.

Education and Skill-set Required

Data, Analytics, Digital, Automation or AI Products (5+ years)

Proven ability to understand existing systems and data landscapes, business processes, integrations, and translate business needs into scalable digital, data, and AI solutions.

Proven experience in business analysis and delivery for enterprise digital, data, analytics and AI solutions within complex, global organizations.

Strong understanding of endtoend data and analytics lifecycles, including data ingestion, modeling, transformation, analytics consumption, and operationalization of insights.

Hands-on experience supporting the design, implementation, and adoption of business applications, and workflowbased digital solutions across multiple business units.

Experience working with analytics, AI, and ML-enabled solutions, including requirements definition, usecase shaping, model integration into business processes, and alignment with platform an