Senior Data Platform Engineer – Data & AI

Equinix; Toronto; On-site; CAD 100,000 - 140,000; Full time

Job summary

Equinix is seeking a Senior Platform Engineer to design and maintain intelligent infrastructures that power AI workloads. Ideal candidates will utilize their expertise in data architecture, distributed systems, and cloud platforms to drive innovation across various teams. Join a mission-driven team that fosters collaboration and embraces diversity.

Benefits

Equitable work environment

Commitment to diversity and inclusion

Opportunities for skill development

Qualifications

• 8–12 years of experience in relevant engineering roles.
• Strong programming experience in Java and Python.
• Deep knowledge of data modeling and distributed systems.

Responsibilities

• Develop and maintain real-time and batch data pipelines.
• Design and develop event-driven architectures.
• Architect and manage multi-cloud platforms.

Skills

Programming in Java

Programming in Python

SQL

Cloud Architecture

Data Engineering

Distributed Systems

API Design

Kubernetes

Streaming Systems

Data Quality Enforcement

Education

Degree in Computer Science or related field

Tools

Apache Kafka

Terraform

Prometheus

Grafana

OpenTelemetry

Job description

Equinix is the world’s digital infrastructure company, operatingover 260 data centersacross 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 hirehardworking people who thrive on solvingchallengingproblems 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 providingan equitable work environmentthat is foundational to our core values as a company and is vital to our success.

Job Summary

We’re 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.

You’ll 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.

Responsibilities

Develop and maintain real-time and batch data pipelines using tools like Airflow, dbt, Dataform, and Dataflow / Spark

Design and develop event-driven architectures using Apache Kafka, Google Pub / Sub, or equivalent messaging systems

Build and expose high-performance data APIs and microservices to support downstream applications, ML workflows, and GenAI agents

Architect and manage multi-cloud and hybrid cloud platforms (e.g., GCP, AWS, Azure) optimized for AI, ML, and real-time data processing workloads

Build reusable frameworks and infrastructure-as-code (IaC) using Terraform, Kubernetes, and CI / CD to drive self-service and automation

Ensure platform scalability, resilience, and cost efficiency through modern practices like GitOps, observability, and chaos engineering

Lead initiatives in data modeling, semantic layer design, and data cataloging, ensuring data quality and discoverability across domains

Implement enterprise-wide data governance practices, schema enforcement, and lineage tracking using tools like DataHub, Amundsen, or Collibra

Guide adoption of data fabric and mesh principles for federated ownership, scalable architecture, and domain-driven data product development

AI & GenAI Platform Integration

Integrate LLM APIs (OpenAI, Gemini, Claude, etc.) into platform workflows for intelligent automation and enhanced user experience

Build and orchestrate multi-agent systems using frameworks like CrewAI, LangGraph, or AutoGen for use cases such as pipeline debugging, code generation, and MLOps

Experience 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 datasets

Create extensible CLIs, SDKs, and blueprints to simplify onboarding, accelerate development, and standardize best practices

Streamline onboarding, documentation, and platform implementation & support using GenAI and conversational interfaces

Collaborate across teams to enforce cost, reliability, and security standards within platform blueprints

Act as a thought leader across engineering by introducing platform enhancements, observability, and cost optimization techniques

Mentor junior engineers and foster a culture of ownership, continuous learning, and innovation

Qualifications

8–12 years of hands-on experience in Platform or Data Engineering, Cloud Architecture, AI Engineering roles

Strong programming background in Java, Python, SQL, and one or more general-purpose languages

Deep knowledge of data modeling, distributed systems, and API design in production environments

Proficiency 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 Platform

Proven experience building scalable, efficient data pipelines for structured and unstructured data

Experience with GenAI / LLM frameworks and tools for orchestration and workflow automation

Experience with RAG pipelines, vector databases, and embedding-based search.

Familiarity with observability tools (Prometheus, Grafana, OpenTelemetry) and strong debugging skills across the stack

Experience with ML Platforms (MLFlow, Vertex AI, Kubeflow) and AI / ML observability tools

Prior implementation of data mesh or data fabric in a large-scale enterprise

Experience with Looker Modeler, LookML, or semantic modeling layers

Why You’ll Love This Role

Drive technical leadership across AI-native data platforms, automation systems, and self-service tools

Collaborate across teams to shape the next generation of intelligent platforms in the enterprise

Work with a high-energy, mission-driven team that embraces innovation, open-source, and experimentation

Equinix 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.