Data Product Engineer

Tiivistelmä työpaikkailmoituksesta: The Data Product Engineer will design, build, deploy and operate scalable data products, pipelines and platform capabilities to transform enterprise source data for analytics, digital solutions and AI. You will implement reusable engineering patterns, data models and end-to-end pipelines with embedded data quality, automated testing, monitoring, observability and governance. The role requires practical skills in SQL and Python, experience with cloud data platforms or lakehouse/warehousing, CI/CD and DataOps practices, data modelling and strong troubleshooting ability, with experience in Microsoft Fabric, Snowflake or Databricks considered valuable. The position is available in multiple global locations (including Espoo, Tampere, Lappeenranta, Krakow, Vadodara, Vilnius, York, Sorocaba or Santiago) with hybrid options, offers competitive compensation and growth opportunities, and applications close on November 15, 2026. Tämä tiivistelmä on luotu tekoälyn avulla. Our world depends on rocks, minerals, metals and other raw materials – the building blocks of modern society. As an industry leader, Metso helps transform these essential materials to enable sustainable modern life. Our solutions and services support everything from renewable energy and electrification to the infrastructure and digital economy shaping our future. Together, we help our customers meet growing demand while driving the industry toward a more sustainable use of the earth’s natural resources. Join nearly 18,000 Metsonites worldwide, each bringing unique expertise and experience to positive change. At Metso, you’re supported by a growth culture built on safety, wellbeing, inclusion and collaboration. This is your opportunity to make an impact and rise above the possible. Job posting end date: 11/15/2026 Introduction We are looking for a Data Product Engineer to design, build, deploy and operate scalable data products, pipelines and platform capabilities that enable analytics, digital solutions and AI across Metso. You will transform data from multiple enterprise source systems into trusted, reusable and business-ready data assets, contributing throughout the data product lifecycle from design and implementation to deployment, monitoring and continuous improvement. This is an opportunity to use modern engineering practices and enterprise data platforms while solving practical business challenges in a global industrial organization. The position is part of Metso’s Data & Analytics organization and reports to the Director, Data Enablement. The preferred locations for this position are some of Metso’s biggest locations: Espoo, Tampere or Lappeenranta, Finland; Krakow, Poland; Vadodara, India; Vilnius, Lithuania; York, USA; Sorocaba, Brazil; or Santiago, Chile. We are happy to offer flexible working arrangements, including hybrid options. Team you’ll belong to You will join Metso’s data engineering community and work closely with Data Architects, Data Engineers, Analytics Engineers, Data Scientists, AI teams and Data Enablement professionals. Together, we create reliable and reusable data products that support reporting, advanced analytics, digital products, and AI. You will collaborate with business stakeholders, application teams, enterprise architecture, platform, integration, infrastructure, and cybersecurity teams to deliver fit-for-purpose solutions. What you’ll do Design, develop and maintain reusable and scalable data products, data models, and end-to-end pipelines for ingestion, transformation, integration, and delivery. Contribute to enterprise data platforms and shared services by implementing reusable engineering patterns, frameworks, and automation capabilities. Improve scalability, performance, reliability and operational efficiency, and support integration between enterprise systems and analytical platforms. Embed data quality, automated testing, validation, monitoring and observability into pipelines and data products. Monitor data availability and operational stability, investigate issues, and implement sustainable corrective solutions. Apply modern software engineering practices, including source control, code reviews, automated testing, CI/CD, DevOps and DataOps. Implement technical governance requirements for metadata, lineage, documentation, access controls, security and compliance. Collaborate with architects, analytics and AI teams, business stakeholders and source-system teams throughout solution design and delivery. What you’ll bring Experience or demonstrated capability in data engineering, data integration, data products, and pipeline development. Practical skills in SQL and Python. Experience with cloud-based data platforms, data warehousing, or lakehouse architectures. Knowledge of data modelling, transformation design, and integration patterns. Experience with CI/CD, DevOps or DataOps practices and secure, maintainable software development. Understanding of automated testing, d