In our new Robotics company, you will strengthen Sustainability’s analytical backbone by building data models, templates, and dashboards that measure performance across climate, circularity, waste, water, energy and materials. You will help set up efficient tools and methods (Power BI, Excel, shared templates), ensure data quality, and enable clear insights for decision‑making across the business. You will also help digitalize and automate our processes, strengthen analytics and decision-making. 

This role is part of ABB’s Robotics business, it bridges IT and sustainability, requiring someone who can code, communicate, and think strategically about data governance. 

By joining us now, you’ll be part of a dynamic and fast-paced organization at the forefront of robotics innovation. As we transition into a separate entity outside the ABB Group, you’ll have the chance to shape the future, grow your career, and work alongside world-class experts in a more agile and entrepreneurial environment. 

The work model for the role is hybrid. #LI-hybrid 

This is a global role; the preferred locations are: Krakow or Västerås, with flexibility for the right candidate 

Your responsibilities: 

• Build Enterprise Analytics Solutions – Develop and maintain scalable dashboards and reports using Power BI, Excel, Snowflake, and Streamlit that track Scope 1–3 emissions, circularity, waste, water, energy, and key sustainability KPIs with advanced data modelling and interactive visualizations 

• Standardize Data Frameworks & Templates – Design and implement reusable data collection processes, templates, and standards across Sustainability, Operations, Supply Chain, HR, Finance, and R&D to ensure consistency, quality, and audit readiness 

• Bridge IT & Sustainability – Translate sustainability business needs into data requirements; collaborate with IS/IT on toolchain decisions, connectors, and data infrastructure while representing the sustainability perspective 

• Ensure Data Integrity & Governance – Set up efficient validation, transformation, and refresh cycles; document calculation rules and assumptions; run quality checks to maintain audit-ready datasets and reliable decision-making 

• Enable Trend Analysis & Insights – Support topic leads with ad hoc analyses, scenario modelling (e.g., decarbonization pathways), and performance dashboards that drive strategy and accountability across the business 

Qualifications for the role: 

Essential skills: 

• Baschelors/ Masters degree in Data/Analytics, Engineering, Sustainability or a related field 

•  3–5 years of hands-on experience in data analysis, business intelligence, or analytics consulting 

• Strong understanding of dimensional modeling, data warehousing concepts, master data management, and building scalable reporting architectures; experience designing data validation frameworks and quality assurance processes 

•  Demonstrated experience managing and reporting ESG metrics, emissions accounting (Scope 1, 2, 3), circularity, waste, water, and sustainability KPIs; familiarity with building templates for multi-stakeholder data collection 

• Proven ability to explain complex technical analyses to non-experts, work effectively in multicultural teams, and adapt quickly as tools, priorities, and business needs evolve; fluency in English 

• Advanced proficiency in Power BI or Tableau, SQL for data querying and transformation, Python or R for scripting and automation, and expert-level Excel (data modeling, pivot tables, automation) is a plus. 

• Excellent communication skills in English  

Essential attributes: 

• Data quality focused – You validate assumptions, document logic, and catch issues early. 

• Systems thinker – You understand data flows and downstream impacts. 

• Self-sufficient builder – You prototype practical solutions independently. 

• Clear communicator – You explain technical topics clearly to non-experts. 

• Adaptable – You stay effective as needs, tools, and priorities change. 

• Collaborative – You partner well with IT while representing sustainability needs.