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Cloud Platform Engineer II, Event Streaming

McDonalds in India

35 - 37 years

Hyderabad

Posted: 31/01/2026

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Job Description

Company Description

McDonalds is the worlds leading global foodservice retailer, serving more than 70 million customers each day in over 100 countries. Our Accelerating the Arches strategy focuses on delivering a more personalized, efficient, and innovative customer experiencefueled by data and technology. The Enterprise Data, Analytics, and AI (EDAA) team is central to this transformation, providing the platforms and capabilities to enable scalable, secure, and intelligent digital solutions.

The Opportunity

As a Platform Engineer, you will build and operate the real-time streaming platform that powers event-driven data movement across McDonalds enterprise systems. You will work hands-on with Confluent Cloud, Google Cloud Pub/Sub, and Amazon MSK to deliver reliable, scalable, and observable streaming solutions in a high-volume, global environment.

This role is ideal for engineers with 35 years of experience who want to deepen their expertise in event-driven architecture, streaming infrastructure, and platform operations within a modern, cloud-native ecosystem.

Key Responsibilities

Qualifications

  • Design, build, and support event-driven and real-time streaming solutions using Confluent Cloud, GCP Pub/Sub, and Amazon MSK .
  • Implement and operate Kafka topics, partitions, consumer groups, and schemas to ensure scalability, reliability, and data integrity.
  • Define and enforce event schema standards , including schema registry usage, compatibility rules, and versioning strategies.
  • Support onboarding of streaming use cases, including topic configuration, access controls, schema validation, and observability setup .
  • Apply delivery semantics, idempotency, and retry strategies to ensure reliable event processing.
  • Operate and support streaming platforms in production, including monitoring, alerting, incident response, and root cause analysis .
  • Collaborate with platform and operations teams to improve automation, reliability, and cost efficiency of streaming infrastructure.
  • Contribute to documentation, runbooks, and continuous improvement of platform standards and operational practices .

Required:

  • Bachelors degree in Computer Science, Engineering, or a related technical discipline.
  • 35 years of experience in platform engineering, data engineering, backend engineering, or Software engineer roles.
  • Strong understanding of Event-Driven Architecture (EDA) principles.
  • Hands-on experience with Kafka-based streaming platforms , including Confluent Cloud or Amazon MSK .
  • Familiarity with cloud-native messaging services , such as Google Cloud Pub/Sub .

Working knowledge of:

Preferred

McDonalds Values

  • Kafka topic design, partitioning, and consumer groups
  • Delivery semantics (at-least-once vs exactly-once) and idempotency
  • Schema Registry and event schema design
  • Experience operating streaming workloads in cloud environments (GCP and/or AWS).
  • Familiarity with scripting or automation (Python, Bash) and infrastructure concepts.
  • Experience with Kafka Connect and managed connectors (non-CDC use cases).
  • Exposure to stream processing tools (e.g., ksqlDB / Apache Flink).
  • Experience with monitoring and observability tools for streaming platforms (e.g., Prometheus, Grafana, Datadog).
  • Understanding of platform security, access controls, and data governance concepts .
  • Experience supporting multi-region or multi-cloud streaming architectures .

Our culture is rooted in our values:

Equal Opportunity Statement

McDonalds is an equal opportunity employer committed to inclusion and diversity. We make all employment decisions based on qualifications, merit, and business needs, and provide reasonable accommodations throughout the hiring and onboarding process.

  • Serve: We put our customers and our people first.
  • Inclusion: We open our doors to everyone.
  • Integrity: We do the right thing.
  • Community: We are good neighbors.
  • Family: We get better together.

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