Data and AI Architect

Your role and responsibilities

The Data & AI Architect is responsible for defining and driving the architecture and design of advanced data and AI/ML solutions for ABB Motion Drive Products. This global role focuses on leveraging digital technologies, data platforms, and artificial intelligence to optimize product performance, enable predictive capabilities, and enhance customer value across the lifecycle of Motion Drive products.

The architect collaborates with global IS team and business functions such as- R&D, product management, Supply Chain, Sales to ensure scalable, secure, and sustainable data-driven solutions that align with Division strategy

The work model for the role is: Hybrid

This role is contributing to the Group IS Security Risk and Compliance global organization. Main stakeholders are Business Area Security Leads, Application Owners and Managers across organization and geographic locations.

You will be mainly accountable for:

1. Develop and maintain end-to-end Data and AI Architecture for Motion Drives Products, integrating enterprise systems (e.g., SAP, PLM, MES) and digital platforms.
2. Define and govern data architecture blueprints across domains such as PLM, SCM, Sales, Smart Factory, ensuring alignment with SAP processes (order-to-cash, plan-to-produce, service).
3. Design scalable data pipelines (real-time and batch) for telemetry and condition monitoring, using tools like Snowflake, Microsoft Fabric, and Databricks.
4. Establish architectural standards and ensure data quality, interoperability, and compliance across edge, cloud, and enterprise systems.

Qualifications for the role:

1. Serve as the Data and AI Architecture Lead for the Division’s transformation programs, aligning architecture strategy with business objectives.
2. Collaborate with business stakeholders, solution architects, and global IS teams to ensure data and AI solutions support key initiatives.
3. Bring 10–15+ years of experience in IT/data roles, including 5–8 years in data architecture, analytics, or AI, with strong exposure to SAP environments.
4. Possess deep technical expertise across data technologies—relational databases, NoSQL, data lakes, streaming, data warehouses, and cloud platforms.
5. Demonstrated experience with data engineering practices such as data pipelines, ETL/ELT, data modelling, metadata management, and master/reference data.
6. Hands-on experience designing or integrating AI/ML models, including feature engineering, model deployment, and lifecycle monitoring.
7. Proficient in SAP technologies (ECC, S/4HANA, BW/4HANA, Data Hub, MDG, Datasphere, SAC) and integrating SAP with non-SAP data systems