Overview

One of the world’s largest employers with locations in more than 100 countries, McDonald’s Corporation has corporate opportunities in Hyderabad.

Responsibilities

• 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.
• 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
• 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.
• Engineer data pipelines and services that power audience segmentation, attribute computation, and activation feeds.
• Ensure efficient data delivery to downstream systems (e.g., CDPs, marketing platforms, APIs) with strict latency and freshness guarantees.
• Build dynamic audience services for behavioral and lifecycle cohorts, rules driven propensity groupings, and event triggered real-time segments.
• Define data contracts and versioning for attributes, traits, and segment definitions to ensure reuse, durability, and safe change management.
• Set and abide by audience governance standards (freshness SLAs, recency/frequency windows, cardinality limits, consent gates) and ensure they’re consistently enforced.
• Partner with Mar Tech and Product to templatize audience playbooks (e.g.,reactivation, onboarding, churn risk, high value, cart abandon).
• Implement comprehensive data quality, validation, and lineage across all audience and profile pipelines.
• Create reference patterns and templates so global markets and channels can integrate quickly and safely.
• Drive CDP capabilities and roadmaps, manage dependencies, and deliver against business outcomes with clear KPIs and executive reporting.
• Build and maintain engineering excellence: testing, automation, code quality, observability, and operational readiness.
• Lead technical execution, review designs and code, mentor engineers on data engineering best practices, and drive disciplined delivery through sprint planning, estimation, and operational follow-through.
• Collaborate with Product, Mar Tech, Loyalty, Architecture, Data Governance, Security, Legal, and Compliance to align roadmaps and ensure privacy-by-design and security-by-default.
• Translate marketing and product activation needs into reusable audience capabilities and APIs.

Qualifications

• 7 - 12 years.