Staff Analytics Engineer

As Staff Analytics Engineer, you will play a pivotal role in shaping the foundations of ABB E-mobility’s data ecosystem by driving scalable analytics engineering practices, strengthening data governance and enabling a federated data community to make better, faster and more trusted decisions. Acting as a technical leader and community enabler, you will help democratize data modeling, harmonize business metrics and accelerate the adoption of AI-powered analytics across the organization.

Your Responsibilities

• Define and evolve the company’s analytics engineering architecture, ensuring scalable, maintainable and interoperable data models that support both business analytics and future AI initiatives across a federated data landscape.
• Drive the analytics engineering strategy and tooling roadmap, partnering closely with the Staff Data Engineer to establish standards, frameworks and best practices that make high-quality data modeling accessible and scalable for the wider data community.
• Lead the standardization and harmonization of business metrics, creating shared definitions and modeling conventions that improve consistency, trust and alignment across functions, domains and reporting use cases.
• Establish and continuously improve data governance and data quality practices, implementing monitoring frameworks, quality controls and accountability models that ensure reliable and trusted data across all domains.
• Coach, mentor and enable data practitioners across the organization, providing training, guidance and hands-on support to data analysts and domain teams while fostering a strong data community and culture of collaboration.
• Deliver complex data modeling and engineering solutions hands-on, developing and optimizing data pipelines, supporting teams that require additional expertise and ensuring efficient, scalable and high-performing data transformations.
• Drive innovation through AI-enabled analytics engineering, building and promoting AI-native workflows, reusable frameworks, agentic AI capabilities and best practices that increase productivity, accelerate delivery and improve self-service analytics adoption.
• Act as a trusted partner to business and technical stakeholders, translating business concepts into scalable data models, influencing decisions across teams and driving alignment through expertise, credibility and collaboration rather than formal authority.

Your Background

• 8+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence or related data disciplines, including demonstrated technical leadership and the ability to operate at the intersection of data engineering and analytics.
• Deep expertise in modern analytics engineering practices, including enterprise data modeling, semantic layer design, metric frameworks and scalable data architecture principles.
• Extensive hands-on experience with modern data transformation frameworks such as dbt, SQLMesh, Dataform or similar technologies, combined with strong expertise in designing and maintaining production-grade data pipelines.
• Advanced SQL proficiency and strong Python skills, with the ability to build, optimize and troubleshoot complex transformations, models and analytics workflows.
• Strong expertise in Azure Databricks, including Unity Catalog, Lakeflow (Declarative Pipelines and Jobs), Databricks SQL and cloud-based data platform architectures.
• Proven experience establishing data governance, data quality and monitoring frameworks, helping organizations improve trust, consistency and ownership of data assets.
• Strong communication, coaching and stakeholder-management capabilities, with a demonstrated track record of mentoring analysts, facilitating alignment across multiple teams and translating business objectives into actionable data solutions.

Nice to Have

• Experience operating within a Data Mesh or federated data organization.
• Experience driving adoption of AI-powered analytics and engineering workflows, including agentic AI frameworks, self-service analytics solutions and platforms such as Claude, ChatGPT, Databricks Genie or similar technologies.
• Familiarity with Azure DevOps, ADX, Grafana, Power BI, SAP Datasphere and SAP Analytics Cloud (SAC).
• Experience supporting high-growth, transformation-driven organizations where data models, processes and governance structures are evolving rapidly.
• Passion for building communities of practice, establishing shared standards and enabling data teams to scale through coaching, collaboration and modern engineering practices.

What’s in it for you?

Work 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 at the core of what we do. We celebrate different experiences and perspectives, and we aim to empower everyone in the creation of sustainable solutions for people all over the world. Our individual differences make us successful.

Compensation Package

The employment framework is based on the National Collective Labour Agreement (CCNL) for the Metalworking Industry, with an indicative level B3 and a minimum gross annual salary starting from € 39.000,00.

The specific level and compensation package will be defined based on the outcome of the selection process (including experience, skills set, and role fit), in accordance with objective, transparent, and gender-neutral criteria, in line with pay equity and equal opportunity principles.

The total compensation package will also include a variable bonus linked to individual and company targets.

About ABB E-Mobility

ABB E-mobility is a world leader in EV charging technology and a partner of choice for the world’s biggest electric vehicle OEMs and nationwide EV charging network operators. With a strong R&D pipeline, our robust product portfolio of innovative holistic solutions – from grid to charge point and domestic installations to large fleet depots – means we are actively enabling the future of E-Mobility, not just predicting it.