Manager, Data Engineering

McDonald’s Corporation

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Quick summary

Work type
On-site
Location
Hyderabad, Telangana, India
Posted
2 days ago
Freshness
Confirmed live today

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Salary context

How this pay compares to similar roles

Similar $178k
$136k most similar roles pay here $229k

This listing doesn't post a salary. Most similar roles pay $144,875–$211,262.

Based on 240 similar postings.

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About McDonald’s Corporation

McDonald’s Corporation is the world's largest fast-food chain by revenue, operating over 40,000 locations in more than 100 countries.

McDonald’s Corporation currently has 49 open roles on FindRole.

Listed pay typically runs $138,207–$172,758 across 24 roles with salary data.

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At a glance

TL;DR · Manager, Data Engineering

Manager, Data Engineering serves as a hands-on individual contributor focused on the development, integration, and operational execution of the Marketer Customer Data Platform (mCDP). This role involves building and maintaining real-time data pipelines, configuring event streams and webhooks, and managing audience segmentations to power marketing and customer engagement initiatives. The successful candidate will manage data schemas, establish secure webhook endpoints, and orchestrate low-latency data flows between mParticle and downstream platforms like Braze. Technical requirements include proficiency in Python or Java, SQL, JSON/AVRO payloads, and REST APIs. The role requires extensive experience with Google Cloud Platform infrastructure, specifically BigQuery, Pub/Sub, Cloud Run, Cloud Functions, GCS, and Terraform. Additionally, the candidate must utilize Git for version control and manage observability tools like New Relic or OpenTelemetry to ensure data hygiene across streaming pipelines.

What you'll do

  • Develop and deploy scalable real-time and batch data pipelines connecting mParticle with marketing platforms and data warehouses.
  • Build and manage integration patterns, including secure webhook endpoints and event-forwarding rules for low-latency data streams.
  • Manage audience segments, user traits, and segment logic within the CDP to ensure accurate customer targeting.
  • Design and maintain GCP infrastructure using BigQuery, Pub/Sub, Cloud Run, Cloud Functions, and Terraform.
  • Implement monitoring, logging, and alerting systems to ensure high platform uptime and automated error handling.
  • Maintain version-controlled codebases and participate in technical reviews and Agile sprint delivery cycles.

What we're looking for

  • Hands-on experience operating and developing within an enterprise Customer Data Platform like mParticle, Segment, or Tealium.
  • Professional experience building data pipelines and managing resources within Google Cloud Platform (GCP) using BigQuery, Pub/Sub, Cloud Functions, and Cloud Run.
  • Proficiency in Python and/or Java with strong skills in SQL, JSON/AVRO payloads, and REST APIs.
  • Experience working with real-time streaming platforms and event-driven data flow principles.
  • Hands-on familiarity with Git version control, CI/CD pipelines, and Infrastructure as Code using Terraform.
  • Experience working in fast-paced Agile/Scrum environments to translate business requirements into technical implementations.
  • Experience integrating customer data flows with omnichannel marketing tools (preferred).
  • Experience with monitoring frameworks, Google Cloud certifications, or familiarity with data privacy frameworks (preferred).

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