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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Manager, Data Engineering - **Company:** McDonald's - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $167,366.0 - $209,207.0 - **Contract:** Permanent contract - **Skills:** Adaptable Database Systems, Application Programming Interfaces (APIs), Amazon Web Services, Application Frameworks, Computing Platforms, Automation of Tests, Cloud Engineering, Continuous Integration, Customer Data Management, Information Engineering, DevOps, Distributed Systems, Data Flow Control, Reliability Engineering, Software Engineering, Data Streaming, Cloud Platform System, Real Time Systems, Apache Spark, Event Driven Architecture, Adobe, Infrastructure Automation Frameworks, Apache Flink, Tealium, Apache Kafka, Data Pipelines, Dynatrace, Devsecops, User Identification, Microservices - **Published:** August 27, 2026 - **Apply:** https://dejobs.org/x/x/661B6039090E4845B78995145BA66358/job/ ## About the Role Preferred Technical QualificationsDeep experience with Customer Data Platforms (mParticle, Segment, Adobe RTCDP, Tealium, or similar).Expertise in large-scale distributed systems, event-driven architecture, and streaming data platforms.Strong experience with Kafka, Spark, Flink, Dataflow, Beam, or related real-time processing frameworks.Experience designing high-volume APIs, microservices, and cloud-native applications.Hands-on expertise with cloud platforms such as GCP, AWS, or Azure.Strong understanding of customer identity, profile unification, consent management, and audience activation patterns.Experience implementing observability solutions, monitoring frameworks, distributed tracing, and reliability engineering practices.Proficiency in modern software engineering practices, including CI/CD, Infrastructure as Code, automated testing, and DevSecOps principles.Proven ability to influence technical direction across multiple engineering teams ## Description We are seeking a highly experienced Senior Engineer to serve as the technical lead for McDonald's Customer Data Platform (mCDP) mParticle ecosystem. This role is a senior engineer responsible for the architecture, engineering direction, scalability, reliability, and evolution of customer data ingestion, identity, audience management, and activation capabilities across digital and restaurant channels.The ideal candidate is both a hands-on engineer and technical leader who can design complex distributed systems, influence architectural decisions across teams, and establish engineering standards that enable scalable, privacy-compliant customer data products globally. Duties Customer Data Platform Architecture & Engineering Lead the architecture and evolution of the mCDP and mParticle ecosystem, delivering scalable, secure, and reliable customer data capabilities. Define standards for data models, event governance, APIs, observability, and platform operations while driving performance, resiliency, and technology innovation. Real-Time Customer Data Processing Design and optimize real-time data pipelines for customer, transactional, and behavioral data. Build scalable streaming architectures, identity resolution frameworks, and low-latency services that enable personalization, audience activation, and cross-channel customer experiences. Audience & Segmentation Platform Engineering Lead the development of enterprise-scale audience and segmentation capabilities. Establish scalable data models and governance standards, optimize audience performance, and create reusable frameworks that support real-time activation while ensuring privacy and consent compliance. Customer Data Products & Platform Quality Own the engineering of customer data products, including profiles, audiences, preferences, and consent records. Establish standards for data quality, reliability, observability, testing, and documentation to ensure scalable and maintainable platform solutions. Technical Leadership & Engineering Excellence Serve as the technical authority for mParticle and customer data platforms. Drive architecture reviews, platform modernization, engineering best practices, and adoption of DevOps, CI/CD, cloud-native, automation, and reliability engineering principles. Cross-Functional Collaboration Partner with Product, MarTech, Loyalty, Security, Privacy, and Engineering teams to deliver scalable customer data solutions. 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