McDonald's Corporation

Chicago, IL

Manager - Data Reliability Engineer

McDonald’s is looking to hire a Manager - Data Reliability Engineering who has a deep understanding of Data Management standards and practices. The role will include work defining and building new technology frameworks for accuracy, validity, reliability, timeliness, relevance, and completeness to improve our data quality and scale our data management practices. A successful candidate has shown experience in managing projects and leading others to highly impactful and timely results as well as being a hands-on individual contributor. You will communicate analyses and recommendations to cross-functional partners and decision makers. The position requires someone that seeks to supplement their skills through the use of project experience, self-study, and ongoing training.

Responsibilities:

  • Improves data reliability through technological means. Develops and implements new technology solutions as needed to ensure ongoing improvement of data reliability and observability
  • 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
  • Engages with application teams to help reengineer ingestion pipelines to be more stable, reliability, and instrumented with monitoring
  • Designs and develops real-time processing solutions for data quality
  • Creates and enhances data solutions that enable seamless integration and flow of data across the data ecosystem
  • Designs software solutions for metadata management, data quality, sensitive data management, and data steward activities.

Requirements:

  • BS in Computer Science or related engineering field and deep experience with AWS infrastructure
  • Experience with creating SQL to investigate data anomalies, patterns and profiling
  • Familiarly with a scripting language, such as python, ruby, bash or equivalent
  • Expert knowledge of quality functions like cleansing, standardization, parsing, de-duplication, mapping, hierarchy management, etc.
  • Expert Knowledge of data, master data and metadata related standards, processes and technology
  • Ability to identify and mitigate data quality issues effectively. Can engage in engineering design discussions on deep root cause analysis and system design for remediation
  • Ability to drive continuous data management quality (i.e. completeness, accuracy) through defined and governed principles
  • Ability to perform extensive data analysis (comparing multiple datasets) using a variety of tools
  • Demonstrated experience in data management & data governance capabilities
  • Working knowledge of relational and dimensional data design and modeling in a large multi-platform data environment
  • Excellent problem solver - use of data and technology to solve problems or answer complex data related questions
  • Excellent communication skills both verbal and written
  • Ability to manage multiple projects under multiple subject areas at once.

Preferred Requirements:

  • Experience with JIRA and Confluence as part of project workflow and documentation tools is a plus
  • Experience with Agile project management methods and terminology a plus
  • Experience with Prometheus, Grafana