Data Engineer II [T500-27045]

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