Data Product Engineer

Metso

1d • Hybrid

About The Position

Metso is seeking 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 the company. The role transforms data from enterprise source systems into trusted, reusable, business-ready assets and contributes across the data product lifecycle, from design and implementation through deployment, monitoring, and continuous improvement.

The position is part of Metso’s Data & Analytics organization and reports to the Director, Data Enablement. The engineer will join Metso’s data engineering community and collaborate with data architects, data and analytics engineers, data scientists, AI teams, Data Enablement professionals, business stakeholders, application teams, enterprise architecture, platform, integration, infrastructure, and cybersecurity teams. Preferred locations are Espoo, Tampere, or Lappeenranta in Finland; Krakow, Poland; Vadodara, India; Vilnius, Lithuania; York, USA; Sorocaba, Brazil; or Santiago, Chile. Hybrid working arrangements are available.

Requirements

• 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, data quality, monitoring, observability, metadata, and data lineage.
• Strong troubleshooting and root-cause analysis skills, with an analytical and structured approach.
• Ability to collaborate with technical and business stakeholders, communicate clearly, and balance technical quality, delivery needs, and business value.
• Strong engineering discipline, quality and product mindset, and orientation toward continuous improvement.

Nice To Haves

• Experience with Microsoft Fabric, Snowflake, Palantir, or Databricks.

Responsibilities

• 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.

Benefits

• Wellbeing programs, occupational healthcare, and supportive services.
• Competitive compensation and performance-based incentives.
• Hybrid working options.
• Learning pathways, mentoring, internal mobility, and global collaboration opportunities.
• A caring, collaborative, and inclusive workplace.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed