Lead Platform Engineer, Data Platform

Overview

Lead the strategy, architecture, and operation of Dyson's enterprise data platform capabilities, enabling data ingestion, storage, processing, governance, analytics, and AI workloads at scale.

What you'll do

• Define and drive the strategy, roadmap, and architecture for Dyson's enterprise data platforms.
• Design, build, and operate scalable data platform services supporting analytics, reporting, AI, and machine learning workloads.
• Lead the implementation of cloud-native data platform solutions across GCP and AWS where required.
• Establish platform standards, governance frameworks, security controls, and operational best practices.
• Enable self-service data capabilities that improve productivity for data engineers, analysts, and data scientists.
• Build and manage platform services for data ingestion, transformation, orchestration, storage, and consumption.
• Collaborate with enterprise architects and business stakeholders to understand data platform requirements and priorities.
• Ensure platforms meet requirements for availability, performance, security, compliance, and cost efficiency.
• Drive automation through Infrastructure as Code, platform engineering, and operational tooling.
• Lead platform modernization initiatives and adoption of emerging technologies in analytics and AI.
• Mentor engineers and develop technical capabilities within the team.
• Manage platform lifecycle, operational support, incident management, and continuous improvement activities.
• Drive FinOps and platform optimization initiatives to maximize value from cloud investments.

What you'll need

• A degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related discipline.
• Significant experience building and operating enterprise-scale data platforms.
• Strong understanding of modern data architecture, data engineering, and analytics ecosystems.
• Experience with cloud-native data platforms and services in Google Cloud Platform, AWS, or Azure.
• Experience with data warehousing, data lakes, lakehouse architectures, and large-scale data processing.
• Strong understanding of data governance, security, privacy, and compliance requirements.
• Experience with data orchestration, automation, and platform engineering practices.
• Knowledge of Infrastructure as Code, CI/CD, and cloud automation frameworks.
• Experience supporting analytics, business intelligence, AI, and machine learning workloads.
• Strong stakeholder management, communication, and leadership skills.
• Excellent problem-solving capabilities and a passion for driving continuous improvement.

Nice to have

• Experience with BigQuery, Databricks, Snowflake, or similar enterprise data platforms.
• Experience with real-time data streaming and event-driven architectures.
• Knowledge of data catalog, metadata management, and data governance solutions.
• Experience supporting enterprise AI and machine learning platforms.
• Cloud certifications in GCP, AWS, Azure, or data engineering disciplines.
• Experience operating platforms within a multi-cloud environment.

Details

• Location: Bangalore IT Capability Centre, India.