Principal Data Engineer
Pubblicato il 25-10-2026 - Abb E-Mobility in Italia
pAs Principal Data Engineer, you will lead the evolution of ABB E-mobility’s data platform and play a key role in scaling our data capabilities across the organization. Working at the center of a federated data ecosystem, you will define the technical foundations, governance standards and engineering practices that enable domain teams to build, own and operate trusted data products while accelerating data-driven decision-making and AI adoption across the business. /p h3Your Responsibilities /h3 pDefine and evolve our self-service data platform, enabling domain teams to build, deploy and operate data products independently while ensuring scalability, reliability, security and ease of use across the organization. /p pProvide technical leadership across the data community, driving architecture decisions that balance domain autonomy with interoperability, consistency and long-term platform sustainability in a Data Mesh environment. /p pDesign and implement federated governance capabilities, embedding data contracts, schema evolution, data quality controls, access management, privacy requirements and security policies directly into platform processes and tooling. /p pBuild and maintain engineering accelerators and paved paths, including reusable templates, CI/CD frameworks, infrastructure modules and developer tooling that simplify adoption and promote engineering best practices across teams. /p pOwn platform performance, reliability and cost optimization, continuously improving operational excellence and ensuring that data services remain scalable, efficient and resilient as adoption grows. /p pPartner with IT and business stakeholders on strategic integration initiatives, providing technical guidance on enterprise data architecture and identifying opportunities to leverage the data platform as a middleware and integration layer.
/p pAct as a hands‑on data engineering consultant, supporting functions with limited technical capabilities by designing and implementing ingestion patterns, pipelines and data solutions while helping build internal expertise. /p pDrive the adoption of AI‑native engineering workflows, developing frameworks, reusable assets and agentic AI capabilities that support end‑to‑end data work from ingestion and transformation to analytics and visualization, with appropriate governance and human oversight. /p h3Your Background /h3 p8+ years of experience in Data Engineering, Data Platform Engineering or related disciplines, including significant technical leadership responsibilities within complex data environments. /p pDeep expertise in Azure Databricks, including PySpark, Delta Lake, Unity Catalog, Lakeflow (Declarative Pipelines and Jobs) and Databricks SQL, with a proven ability to architect and scale modern cloud data platforms. /p pStrong software engineering skills in Python and SQL, with hands‑on experience designing, developing, optimizing and maintaining production‑grade data pipelines and data products. /p pProven experience with Infrastructure as Code and platform automation, including Terraform, Databricks Asset Bundles, CI/CD pipelines and modern developer workflows, ideally within Azure DevOps environments. /p pStrong understanding of data governance,
security and access management, including hands‑on experience implementing enterprise‑grade controls across Azure and Databricks environments using tools such as Microsoft Entra ID. /p pExtensive experience with data integration patterns, including batch ingestion, API‑based integrations, streaming architectures and large‑scale data processing in distributed environments. /p pExcellent communication, stakeholder management and influencing skills, with a demonstrated ability to drive alignment across teams, mentor technical communities and lead initiatives through expertise and collaboration rather than formal authority. /p h3Nice to Have /h3 pExperience building and scaling Data Mesh or federated data platforms. /p pFamiliarity with Azure Data Explorer (ADX), Grafana, Power BI, SAP Datasphere and SAP Analytics Cloud (SAC). /p pExperience defining platform standards, developer enablement strategies and community‑driven engineering practices. /p pHands‑on experience integrating AI into engineering workflows, including agentic AI frameworks, coding assistants, automated development processes and AI‑enhanced data operations. /p pExperience supporting organizations undergoing significant digital, data and business transformation, with a strong passion for innovation, knowledge sharing and technical excellence. /p h3What’s in it for you? /h3 pWork with the best specialists in their field, in a diverse environment with unparalleled global reach. Feel inspired by our fast growth. You will have the accountability to own your part in enabling a future of sustainable and efficient mobility. You can also count on a competitive compensation package in line with your capabilities and experience. Diversity, inclusion, and equal opportunities are