Data Engineer III

McDonald's Corporation•Chicago, IL

1d•$138,207 - $172,758

About The Position

We are seeking a highly skilled Data Engineer III to join the mCDP mParticle engineering team. This role is responsible for designing, developing, and maintaining customer data pipelines, audience-building capabilities, activation feeds, and platform integrations that power customer engagement experiences across digital and restaurant channels. The ideal candidate is a hands-on engineer with strong data engineering and analytics experience who can independently own initiatives from requirements through production deployment. This engineer will partner closely with Product, MarTech, Analytics, and Engineering teams to translate complex business requirements into scalable technical solutions while ensuring reliability, quality, and maintainability across the customer data ecosystem. This role requires strong technical execution, problem-solving, and the ability to navigate ambiguity while delivering high-quality solutions with minimal oversight.

Requirements

5-8+ years of professional Data Engineering experience.
3+ years working with cloud-native data platforms on GCP, AWS, or Azure.
Expert-level SQL, including complex joins, window functions, optimization, and large-scale data analysis.
Strong experience designing and developing ETL/ELT pipelines.
Strong knowledge of programming languages such as Python, SQL, JavaScript or Node.js
Experience with DevOps & Reliability - CI/CD pipelines, Git-base development workflows.
Experience with streaming and data processing (Kafka, Spark/PySpark, Flink, Dataflow / Apache Beam)
Experience supporting Customer Data Platforms such as mParticle, Segment, Adobe RTCDP, Braze, Tealium, or similar platforms.
Experience implementing customer attributes, audience segmentation, identity resolution, traits, and activation feeds.

Nice To Haves

Experience with GCP preferred (BigQuery, Pub/Sub, Dataflow, Cloud Run, Cloud Storage)

Responsibilities

Design, develop, test, and support customer data pipelines that ingest, transform, enrich, and distribute customer data across the mParticle ecosystem.
Support onboarding of new data sources, attributes, customer events, and downstream activation integrations.
Build and maintain data pipelines that power audience segmentation, customer traits, profile enrichment, and activation use cases.
Implement audience qualification and refresh logic supporting both batch and real-time use cases.
Configure and support activation feeds to downstream marketing and personalization platforms, ensuring data accuracy and timeliness.
Partner with Product and MarTech teams to implement audience strategies including onboarding, re-engagement, loyalty, churn mitigation, and personalization use cases.
Build scalable solutions using technologies such as Kafka, Spark Structured Streaming, Flink, Dataflow, or equivalent distributed processing platforms.
Support event-driven integration patterns that enable low-latency customer activation and personalization scenarios.
Assist with implementation and maintenance of eventing platforms such as Kafka, Confluent, or managed messaging services.
Implement automated validation, reconciliation, and quality checks across customer data pipelines.
Maintain documentation for data flows, mappings, business logic, and operational procedures.
Independently manage and deliver complex engineering work items with minimal supervision.
Collaborate with team members during sprint planning, solution design, testing, and deployment activities.
Perform code reviews and contribute to engineering best practices across the team.