McDonald's Global Technology - Data & Analytics team is looking to hire a Sr Manager, Data Engineering to lead and own multiple products within the Global Data & Analytics team, from an engineering lead standpoint, and to globally improve and progress McDonalds to a world class data product organization.
Requirements
- 10+ years of hands-on experience in data engineering, specifically with AWS & GCP backend tech stack, including but not limited to S3, Redshift, Glue, Lambda, GCS, BigQuery, Cloud Functions, Cloud Run, etc.
- 8+ years of technically focused experience in related technologies and languages (Web Services, Java, XML, S3, NoSQL, Kafka, Spark, etc.)
- 4+ years of experience in Master Data Management (MDM), Data Governance, and Data Quality domains, and MDM tools.
- Hands-on with Event, Workflow and Application driven Data Architecture. API and Microservices management
- Working knowledge of cloud-based data systems, including AWS and GCP
- 7+ years of experience with DevOps and data reliability engineering
- 7+ years of hands-on experience with data modeling, ETL / ELT development, and data integration techniques (including real time data integration and processing).
Responsibilities
- Build and maintains relevant and reliable data products that support the business needs. Develops and implements new technology solutions as needed to ensure ongoing improvement with data reliability and observability in-view
- Collaborate with Enterprise Architecture to launch scalable and reliable data solutions, support system integration efforts, and create operational efficiencies through automation and process improvements
- Participates in new software development engineering. Helps to define business rules that determines the quality of data, assists the product owner in writing test scripts that validates business rules, and performs detailed and rigorous testing to ensure data quality
- Develops a solid understanding of the technical details of data domains, and clearly understands what business problems are being solved
- Owns engineering modules, functionalities and supports them throughout the data development lifecycle
- Develop the data product’s target technical blueprint and key technology decisions to deliver the roadmap
- Designing and developing end-to-end data pipelines and ETL processes to extract, transform, and load data from various sources into cloud data storage solutions (e.g., S3, Redshift, GCS, BigQuery).
Other
- Lead and own multiple products within the Global Data & Analytics team, from an engineering lead standpoint.
- Responsible for prioritizing multiple technical product backlogs, balancing new features, functional requirements, non-functional requirements and requests across teams and coordinating deployments with other Product Owners in the Data & Analytics team.
- Requires the experience or proven aptitude to develop detailed domain knowledge of multiple products.
- Oversee what work goes to development squads as the lead technology representative and decision-maker, working in tandem with the product team.
- Partner with business customers and stakeholders to define and deliver the associated technical data product solutions using a mix of internal and external (vendor) resources and products and ensure successful integration with existing McDonald’s systems.
