Job Title

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.Job Description: Sr. Manager, Data Engineering – RealTime CDPPosition Summary:We are seeking a Sr. Manager, Data Engineering to lead the engineering strategy and delivery for our RealTime Customer Data Platform (CDP) with a primary focus on audience building and segmentation. You will own low latency ingestion, identity resolution, audience/segment services, latency ingestion, identity resolution, audience/segment services, consent targeting frameworks, and aware targeting frameworks, and high-performance activation APIs that power omnichannel experiences, loyalty, and marketing operations at global channel experiences, loyalty, and marketing operations at global scale.Primary Responsibilities:RealTime CDP & StreamingAudience Building & SegmentationCustomer Data Products & QualityLeadership & DeliveryCross Functional CollaborationWho We’re Looking For:A Handson, strategic 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.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.Establish standards for observability, SLAs/SLOs, schema evolution, lineage, and cost efficiency across streaming and batch paths.Lead the design and operation of a scalable audience/segmentation platform supporting both real-time and batch segment creation and refresh.Build dynamic audience services for behavioral and lifecycle cohorts, rules driven propensity groupings, and event triggered Realtime time segments.Define data contracts and versioning for attributes, traits, and segment definitions to ensure reuse, durability, and safe change management.Set 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, cartabandon).Own high-fidelity customer data products (profiles, attributes, segments, preferences, consent) backed by clear SLOs and documentation.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.Lead, mentor, and grow global data engineering teams focused on streaming, segmentation, activation, and data product engineering.Drive multisugar roadmaps, manage dependencies, and deliver against business outcomes with clear KPIs and executive reporting.Champion engineering excellence: testing, automation, code quality, observability, and operational readiness.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.SQL Very Strong proficiency in native SQL, has used Big Query or Athena Advanced performance tuning on large datasets.Languages: Python (primary), JavaScript, Node.js plus Java.Streaming & Processing: Kafka, Flink, Spark / Pyspark, Dataflow/Beam.Audience/Segmentation: Handson experience building audience engines, cohort generation logic, and audience APIs for activation.Data Platforms: GCP, Databricks; Big Data ecosystems (Hadoop, Lakehouse patterns); NoSQL; columnar formats (Parquet).Cloud: GCP preferred (Pub/Sub, Big Query, Dataflow, Cloud Run); AWS/Azure acceptable.Pipelines & Orchestration: ETL/ELT, Airflow/Luigi, CI/CD for data.Data Management: Metadata management, schema evolution, data contracts, lineage.Governance & Reliability: Observability, SLAs/SLOs, validation, consent/privacy controls.10–15 years in largescale Data Engineering / Distributed Systems.5+ years leading engineering teams/squads.4+ years with GCP or AWS (GCP preferred).3+ years working on real time customer data and/or segmentation platforms.Experience with CDPs (mParticle, Adobe RTCDP, Braze, Tealium).Designing Realtime audience builders, rule engines, and activation frameworks.Multiregional deployments, data residency, and consent management at global scale.Strong stakeholder communication; ability to simplify technical concepts for marketers and product leaders.Systems thinker with strong architectural judgment and influence.Work location: Hyderabad, IndiaWork pattern: Full time role.Work mode: Hybrid.