About McDonald’s
One of the world’s largest employers with locations in more than 100 countries, McDonald’s Corporation has corporate opportunities in Hyderabad. Our global offices serve as dynamic innovation and operations hubs, designed to expand McDonald's global talent base and in-house expertise. Our new office in Hyderabad will bring together knowledge across business, technology, analytics, and AI, accelerating our ability to deliver impactful solutions for the business and our customers across the globe.
Department Overview
We are seeking a Manager, Data Engineering to lead hands-on technical delivery for key components of our RealTime Customer Data Platform (CDP). This role is deeply focused on core data engineering: building scalable streaming pipelines, managing stateful processing, ensuring data quality and reliability, and operating production-grade data systems
Skills Required
Kafka, Confluent, Pub/Sub, AWS, Azure, GCP, Docker, Kubernetes, CICD, CI/CD, Java
Experience Range
7 - 12 years
Duties
RealTime CDP & Streaming
- Architect, build, and operate high-throughput, low-latency streaming pipelines for clickstream, transactional, and behavioral data using Kafka, Flink, Spark Structured Streaming, or Dataflow/Beam.
- Design stateful stream processing for sectorization, windowing, deduplication, enrichment, and late-arriving data handling.
Core Data Engineering
- Design and implement robust data models for events, customer attributes, and derived features.
- Manage schema evolution, backward compatibility, and data contracts. Build scalable batch pipelines to support backfills, reprocessing, and historical precomputation aligned with real-time logic.
- Data Quality, Reliability & Operations
- RealTime CDP & Streaming
- Audience Building & Segmentation
- Customer Data Products & Quality
- Leadership & Delivery
- Cross Functional Collaboration.
Show the full description
- Work location: Hyderabad, India
- Work pattern: Full time role.
- Work mode: Hybrid
Who We’re Looking For
A hands-on, full stack Data Engineering leader who can elevate real time customer data and audience/segmentation capabilities, scale them globally, and develop worldclass engineering teams that deliver privacy safe, high-performance activation.
- Implement data quality checks (completeness, validity, timeliness), pipeline-level SLAs/SLOs, and end-to-end observability.
- Own production readiness including monitoring, alerting, capacity planning, and on-call support with SRE partners.
- Architect and scale real-time pipelines for clickstream, transactional, and behavioral data using Kafka, Flink, Spark Structured Streaming, or Dataflow/Beam.
- Design and evolve customer event models, session-inaction, and cross channel stitching to maintain a unified, channel stitching to maintain a unified, privacy aware customer view.
- Implement low latency activation APIs used by apps, web, CRM, loyalty, kiosks, and marketing orchestration platforms.
- Implement Eventing frameworks like managed Kafka or Confluent
- Establish standards for observability, SLAs/SLOs, schema evolution, lineage, and cost efficiency across streaming and batch paths.
