Principal Software Engineer

Who are we? Equinix is the world's digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future. Help us challenge assumptions, uncover bias, and remove barriers-because progress starts with fresh ideas. You'll find belonging, purpose, and a team that welcomes you-because when you feel valued, you're empowered to do your best work. Job Summary As a Principal Data Engineer at Equinix, you will be responsible for driving end-to-end delivery of enterprise-scale data solutions on Google Cloud Platform. This role combines hands-on technical expertise, requiring you to design sophisticated system architectures, lead cross-functional initiatives, and mentor data engineers. You will act as a trusted technical advisor for the team championing innovation across GCP, Data Engineering, AI, Agentic AI, and Model Context Protocol (MCP). The ideal candidate possesses unparalleled technical depth, exceptional strategic thinking, and a demonstrated history of delivering transformational data platform capabilities at a global scale. Responsibilities System Design & Architecture Leadership Architect and evolve cloud-native, petabyte-scale data platforms and data products, with clearly defined and measurable SLOs for data freshness, availability, and reliability Design data solutions balancing scalability, performance, cost, and operational excellence through clear architectural trade-offs Establish reference architectures, architectural guardrails, and engineering standards adopted organization-wide Lead architectural governance across all data engineering squads, ensuring consistency, scalability, and security Evaluate and adopt emerging technologies (including Agentic AI/LLM and real-time systems) to improve engineering productivity and business outcomes Drive adoption of domain-oriented data architecture (e.g., data mesh principles) across business domains to enable ownership, consistency, and reuse Technical Solutioning & Innovation Design scalable data solutions using modern cloud-native technologies (e.g., BigQuery, Dataflow, dbt/Dataform, Pub/Sub), selecting the right tools based on problem context Own end-to-end delivery of complex data engineering initiatives from design through production, and continuous evolution. for real-time streaming, event-driven architectures, and unified batch-streaming pipelines at petabyte scale Evaluate and adopt AI/LLM capabilities to improve engineering productivity and enable intelligent data consumption, using standard interfaces (e.g., Model Context Protocol) to integrate AI with data systems Establish engineering excellence frameworks covering performance engineering, cost governance, reliability, and observability Lead proof-of-concept and rapid prototyping of breakthrough technologies before scaling org-wide Team Leadership & Mentorship Serve as a technical role model and multiplier - elevating the capabilities of Senior Staff, Staff, and Data Engineers across the organization Lead org-wide engineering communities of practice and knowledge-sharing initiatives Partner with engineering managers and HR to drive technical hiring strategy and raise the engineering talent bar Drive culture of engineering excellence, innovation, and continuous learning Establish mentorship programs that systematically grow the next generation of technical leaders Data Governance & Compliance Architect automated data quality platforms, end-to-end lineage tracking, and enterprise metadata management systems Ensure compliance with GDPR, SOX, and emerging global data regulations through proactive architecture and policy design Lead privacy-by-design initiatives, zero-trust data access models, and data anonymization at scale Establish cross-cloud security standards and enforce them through automated policy guardrails Design privacy-prese