Platform Engineer – Data

Who are weEquinix is the worlds digital infrastructure companyxc2xae operating over 260 data centers across the globe Digital leaders harness Equinix s trusted platform to bring together and interconnect foundational infrastructure at software speed Equinix enables organizations to access all the right places partners and possibilities to scale with agility speed the launch of digital services deliver world-class experiences and multiply their value while supporting their sustainability goals Our culture is based on collaboration and the growth and development of our teams We hire hardworking people who thrive on solving challenging problems and give them opportunities to hone new skills and try new approaches as we grow our product portfolio with new software and network architecture solutions We embrace diversity in thought and contribution and are committed to providing an equitable work environment that is foundational to our core values as a company and is vital to our success Job SummaryWere looking for a Senior Platform Engineer with a strong foundation in data architecture distributed systems and modern cloud-native platforms to architect build and maintain intelligent infrastructure and systems that power our AI GenAI and data-intensive workloads Youll work closely with cross-functional teams including data scientists ML software engineers and product managers play a key role in designing a highly scalable platform to manage the lifecycle of data pipelines APIs real-time streaming and agentic GenAI workflows while enabling federated data architectures The ideal candidate will have a strong background in building and maintaining scalable AI Data Platform optimizing workflows and ensuring the reliability and performance of Data Platform systems ResponsibilitiesPlatform Cloud EngineeringDevelop and maintain real-time and batch data pipelines using tools like Airflow dbt Dataform and Dataflow SparkDesign and develop event-driven architectures using Apache Kafka Google Pub Sub or equivalent messaging systemsBuild and expose high-performance data APIs and microservices to support downstream applications ML workflows and GenAI agentsArchitect and manage multi-cloud and hybrid cloud platforms e g GCP AWS Azure optimized for AI ML and real-time data processing workloadsBuild reusable frameworks and infrastructure-as-code IaC using Terraform Kubernetes and CI CD to drive self-service and automationEnsure platform scalability resilience and cost efficiency through modern practices like GitOps observability and chaos engineeringData Architecture GovernanceLead initiatives in data modeling semantic layer design and data cataloging ensuring data quality and discoverability across domainsImplement enterprise-wide data governance practices schema enforcement and lineage tracking using tools like DataHub Amundsen or CollibraGuide adoption of data fabric and mesh principles for federated ownership scalable architecture and domain-driven data product developmentAI GenAI Platform IntegrationIntegrate LLM APIs OpenAI Gemini Claude etc into platform workflows for intelligent automation and enhanced user experienceBuild and orchestrate multi-agent systems using frameworks like CrewAI LangGraph or AutoGen for use cases such as pipeline debugging code generation and MLOpsExperience in developing and integrating GenAI applications using MCP and orchestration of LLM-powered workflows e g summarization document Q A chatbot assistants and intelligent data exploration Hands-on expertise building and optimizing vector search and RAG pipelines using tools like Weaviate Pinecone or FAISS to support embedding-based retrieval and real-time semantic search across structured and unstructured datasetsEngineering EnablementCreate extensible CLIs SDKs and blueprints to simplify onboarding accelerate development and standardize best practicesStreamline onboarding documentation and platform implementation support using GenAI and conversational interfacesCollaborate across teams to enforce cost reliability and security standards within platform blueprints Work with engineering by introducing platform enhancements observability and cost optimization techniquesFoster a culture of ownership continuous learning and innovationQualifications5 years of hands-on experience in Platform or Data Engineering Cloud Architecture AI Engineering rolesStrong programming background in Java Python SQL and one or more general-purpose languagesDeep knowledge of data modeling distributed systems and API design in production environmentsProficiency in designing and managing Kubernetes serverless workloads and streaming systems Kafka Pub Sub Flink Spark Experience with metadata management data catalogs data quality enforcement and semantic modeling automated integration with Data PlatformProven experience building scalable efficient data pipelines for structured and unstructured dataExperience with GenAI LLM frameworks and tools for orchestration and workflow automationExperience with RAG pipelines vector databases and embedding-based searchFamiliarity with observability tools Prometheus Grafana OpenTelemetry and strong debugging skills across the stackExperience with ML Platforms MLFlow Vertex AI Kubeflow and AI ML observability toolsPrior implementation of data mesh or data fabric in a large-scale enterpriseExperience with Looker Modeler LookML or semantic modeling layersWhy Youll Love This RoleDrive technical leadership across AI-native data platforms automation systems and self-service toolsCollaborate across teams to shape the next generation of intelligent platforms in the enterpriseWork with a high-energy mission-driven team that embraces innovation open-source and experimentationEquinix is committed to ensuring that our employment process is open to all individuals including those with a disability If you are a qualified candidate and need assistance or an accommodation please let us know by completing Equinix is an Equal Employment Opportunity and in the U S an Affirmative Action employer All qualified applicants will receive consideration for employment without regard to unlawful consideration of race color religion creed national or ethnic origin ancestry place of birth citizenship sex pregnancy childbirth or related medical conditions sexual orientation gender identity or expression marital or domestic partnership status age veteran or military status physical or mental disability medical condition genetic information political organizational affiliation status as a victim or family member of a victim of crime or abuse or any other status protected by applicable law