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: Data Engineering II – RealTime CDP
Position Summary:
We are seeking a Data Engineer II preferably Full Stack Engineer, to focus on core data engineering work within our RealTime Customer Data Platform (CDP). This role emphasizes building, testing, and operating data pipelines while developing strong fundamentals in streaming and distributed data systems.
Primary Responsibilities:
- RealTime CDP & Streaming
- Audience Building & Segmentation
- Customer Data Schemas & Quality
- Leadership & Delivery
- Cross Functional Collaboration
Who We're Looking For:
A hands-on, full stack Data Engineering leader who can build real time and batch customer data pipelines and build audience/segmentation capabilities, scale them globally, and develop worldclass engineering teams that deliver privacy safe, high-performance activation.
- Build 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-ization, 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.
- Build and maintain observability, SLAs/SLOs, schema evolution, lineage, and cost efficiency across streaming and batch paths.
- 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.
- Setup and configure audience governance rules (freshness SLAs, recency/frequency windows, cardinality limits, consent gates) and ensure they're consistently enforced.
- Create and maintain audience playbooks (e.g., reactivation, onboarding, churn risk, high value, cart abandon).
- Deepen market relationships to better understand segmentation and activation needs.
- Ideate and propose new capabilities for testing and market validation.
- Create customer data schemas (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.
- Enhance collaboration with other product teams to proactively drive and align requirements.
- Take active role in leading design discussions, especially around CDP capabilities.
- Improve oversight of vendor resources to ensure timely and quality delivery.
- Ideate capabilities and roadmaps, manage dependencies, and deliver against business outcomes with clear KPIs and executive reporting.
- Build 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.
- 5-7 years in largescale Data Engineering / Distributed Systems.
- 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 real time audience builders, rule engines, and activation frameworks.
- Multi regional 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, India
Work pattern: Full time role.
Work mode: Hybrid
