Platform Owner, Databricks Enterprise Platform

KONE Technology and Innovation Unit (KTI) is where we combine the physical world - escalators and elevators - with smart and connected digital systems. We are changing and improving the way billions of people move within buildings every day. We are on a mission to expand and develop new digital solutions that are based on emerging technologies.

KONE IT is a global team of expert professionals working along with business functions and area teams to develop new capabilities and enable new business opportunities. We are trusted partners of KONE business lines and functions to develop, transform, manage and run their information technology solutions. We support KONE in its digital transformation journey by introducing e.g. digital cloud-based IT services, artificial intelligence (AI) and automation to support productivity, business growth and technological disruption. Sustainability, curious mindset and innovation are at the core of everything we do, and this makes us an integral part of KONE's success.

Platform Owner, Databricks Enterprise

Ready to shape the future of enterprise data and AI Join the KONE IT Enterprise Data & Analytics team in Chennai, India, and help build the digital data backbone of KONE's transformation. Our team is accelerating Data Foundation, KONE's modern cloud data and AI architecture built on Databricks and AWS, to unlock scalable AI, advanced analytics, and digital innovation across the business.

Databricks enterprise Platform Owner is responsible for maximizing the business value, reliability, security, and adoption of the Databricks enterprise platform across its lifecycle, in alignment with the Platform Manager's direction. Working with stakeholders, enterprise platform users, data engineers, analytics teams, security, architecture, and operations, the Platform Owner translates business and technical needs into a clear platform roadmap and prioritized backlog. The role ensures that the Databricks enterprise platform provides secure, scalable, governed, and cost-efficient capabilities for data engineering, analytics, machine learning, and AI use cases.

The Databricks enterprise platform includes workspaces, compute, governance, data access, developer enablement, observability, and platform operations capabilities supporting enterprise data and AI workloads. Stakeholders and users may include data product teams, AI teams, platform engineers, security and compliance functions, enterprise architecture, operations, finance, and other technology or business teams using the platform.

The Databricks enterprise platform Owner guides platform teams to balance platform stability, governance, usability, and speed of delivery. The role follows platform KPIs such as availability, adoption, delivery performance, security posture, cost efficiency, and user satisfaction, and drives corrective actions when needed, escalating strategic trade-offs to the Platform Manager. The Platform Owner applies agile, platform engineering, DevOps, and FinOps principles to improve developer experience, accelerate value realization, and ensure the platform evolves in line with enterprise data and AI strategy.

Core responsibilities:

• Own the Databricks enterprise platform vision, roadmap, and backlog in alignment with the platform manager and enterprise data, analytics, and AI strategy, ensuring investments maximize business value across the platform lifecycle.
• Partner with stakeholders and the platform manager to define and prioritize platform capabilities such as workspace standards, compute models, CI/CD enablement, data access patterns, developer tooling, ML/AI enablement, and self-service experiences.
• Be accountable for platform governance by ensuring consistent implementation of catalog, schema, access control, lineage, auditability, and data sharing practices, including adoption of Unity Catalog and related governance controls where applicable.
• Ensure the platform is secure and compliant by working with cybersecurity, identity, infrastructure, and architecture stakeholders on access models, service principals, secrets handling, network controls, environment segregation, and policy enforcement.
• Guide the team toward a platform engineering mindset by building reusable platform services, guardrails, templates, and automation that help product and domain teams use Databricks effectively and safely.
• Own platform operations and reliability, including service levels, observability, incident follow-up, environment health, capacity and quota planning, and corrective actions needed to sustain stable operations.
• Drive cost transparency and optimization across the platform lifecycle, including budgeting input, usage visibility, tagging/chargeback principles, compute policy governance, license considerations, and FinOps-oriented decision making in alignment with the Platform Manager.
• Ensure platform changes are translated into clear releases, standards, and enablement so that teams can deploy and adopt new features smoothly across development, test, and production environments.
• Continuously monitor platform adoption and user experience, gather feedback from engineering, analytics, and AI teams, and turn feedback into prioritized improvements to increase usability and value realization.
• Apply agile, DevOps, and automation practices to improve release quality, delivery speed, repeatability, and environment consistency, including support for source control and CI/CD patterns.
• Collaborate with enterprise architecture and data/domain leaders on platform standards, reference patterns, and roadmap dependencies to ensure Databricks fits into the broader enterprise technology landscape.
• Guide team members on platform priorities, operational practices, governance expectations, and change management while promoting continuous improvement in both the platform and ways of working.
• Support adoption of new Databricks capabilities relevant to the enterprise, including structured data, streaming, machine learning, and AI-related platform services, based on business needs and platform readiness.

Professional requirements

• A master's degree in engineering, computer science, management information systems, or a related field.
• 12-15+ years of experience in platform ownership, product management, data platform engineering, or a closely related role, including work with agile ways of working.
• Demonstrated experience working with complex enterprise platforms in a global environment experience with Databricks, cloud data platforms, or lakehouse technologies is strongly preferred.
• Strong understanding of enterprise data platforms, data engineering, analytics, and AI/ML use cases, with the ability to connect platform capabilities to business outcomes.
• Solid knowledge of platform/product management practices and hands-on understanding of Databricks or similar lakehouse/data platform concepts across governance, operations, and user enablement.
• Ability to translate between business, platform engineering, security, architecture, and operations viewpoints.
• Good understanding of platform architecture principles, environment design, access models, and developer experience for shared enterprise platforms.
• Knowledge of governance, metadata, lineage, and access control concepts, including how governed data access supports compliance and trusted analytics.
• Strong familiarity and experience with agile, DevOps, FinOps automation, observability, and value-driven prioritization.
• Strong stakeholder management, communication, and influencing skills in a global and cross-functional environment using English language.

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