Lead Data Product Engineer

Metso • Tampere, PA

1d • Hybrid

About The Position

We are looking for a Lead Data Product Engineer to lead the development and continuous improvement of Metso’s enterprise data engineering capabilities, practices and standards. You will provide technical leadership across data products, platforms and integration solutions, helping ensure our engineering solutions are scalable, reliable, secure, and aligned with enterprise architecture and business objectives. This is an opportunity to shape how data engineering is done across Metso and enable high-quality data products for analytics, digital solutions, and AI. The role combines hands-on technical expertise with technical leadership, coaching, and cross-functional collaboration.

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.

You will be part of Metso’s Data & Analytics organization, working closely with Data Architects, Data Engineers, Reporting Engineers, Data Scientists, AI teams, and other Data professionals. Together, we create trusted, reusable, and business-ready data products that enable data-driven decision-making, digitalization, and AI across Metso.

You will work in a global matrix environment with business stakeholders, product and platform teams, solution owners, architects, and application teams.

Requirements

• Extensive experience designing, developing and operating enterprise-scale data solutions.
• Strong expertise in data engineering, data integration, and data product development.
• Experience with cloud data platforms, distributed data processing, lakehouse architectures, and data warehousing.
• Proven ability to lead technically complex implementations or engineering initiatives.
• Strong software engineering practices, including source control, code reviews, automated testing, and CI/CD.
• Experience with DataOps, infrastructure-as-code, observability and operational reliability.
• Understanding of data quality, metadata, lineage, security and governance requirements.
• Ability to translate business and architectural requirements into practical solutions, influence technical decisions, and coach technical professionals.
• Strong analytical, problem-solving, collaboration, communication, and stakeholder management skills.

Nice To Haves

• Experience with platforms such as Microsoft Fabric, Snowflake, Palantir, and Databricks is considered valuable.

Responsibilities

• Lead the design and implementation of enterprise-scale data products, pipelines, and integration solutions.
• Define and maintain data engineering standards, frameworks, patterns, and reusable assets that improve quality, consistency, and efficiency.
• Guide to the evolution of enterprise data platforms and scalable solutions for data ingestion, transformation, orchestration, and serving.
• Establish engineering patterns for batch, streaming, event-driven and AI-enabled workloads, improving performance, scalability, reliability and cost efficiency.
• Embed data quality, metadata, lineage, observability, automated testing, CI/CD and infrastructure-as-code into engineering delivery.
• Partner with Data Architects and delivery teams to translate architectural designs into robust, maintainable and production-ready solutions.
• Review solution designs, resolve complex technical challenges, and support performance optimization and production reliability.
• Coach and mentor technical professionals, facilitate knowledge sharing and act as trusted technical advisors to product teams and strategic initiatives.

Benefits

• Purpose-led work: Contribute to enabling sustainable modern life and transforming the industry.
• Wellbeing: Access to wellbeing programs, occupational healthcare, and supportive services.
• Rewards: Competitive compensation and performance-based incentives.
• Flexibility: Hybrid working options to support balance and productivity.
• Growth: Learning pathways, mentoring, internal mobility, and global collaboration opportunities.
• Culture: A caring, collaborative, and inclusive workplace committed to helping you thrive.

What This Job Offers

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