Manager - Data Engineer - Data & Analytics
McDonald’s evolving Accelerating the Arches growth strategy puts our customers and people first, and uses our competitive advantages to strengthen our brand. We are recognized on lists like Fortune’s Most Admired Companies and Fast Company’s Most Innovative Companies.
Doubling Down on the 4Ds (Delivery, Digital, Drive Thru, and Development)
Our growth pillars emphasize the meaningful role technology plays as the leading, global omni-channel restaurant brand. Technology enables the organization through digital technology, and improving the customer, crew and employee experience each and every day.
Global Technology forging the way
Leading the digitization of our business is the Technology organization made up of intrapreneurs who build industry defining tech using the latest innovations and platforms, like AI and edge computing to deliver on the next set of cutting-edge opportunities for the business. At McDonald’s you get to solve technology innovation challenges at an incredible scale, and work across global teams who are always eager for a challenge. This provides access to exciting career paths for technologists. It’s bonus points when you get to see your family and friends use the tech you build at their favorite McD restaurant.
McDonald’s Global Technology - Data & Analytics team is looking to hire a Data Engineer who has a deep understanding of data product lifecycle, standards and practices. You will be responsible for building scalable and efficient data solutions to support the company's data products and analytics initiatives. As a Data Engineer, you will collaborate with data scientists, analysts, and other cross-functional teams to ensure the availability, reliability, and performance of data systems. Your expertise in cloud computing platforms, technologies and data engineering best practices will play a crucial role in delivering high-quality data products and enabling data-driven decision-making.
- Builds 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.
- 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
- Designing and developing data pipelines and ETL processes to extract, transform, and load data from various sources into AWS data storage solutions (e.g., S3, Redshift, Glue).
- Implementing and maintaining scalable data architectures that support efficient data storage, retrieval, and processing.
- Collaborating with data scientists and analysts to understand data requirements and ensure data accuracy, integrity, and availability.
- Building and optimizing data integration workflows to connect data from different systems and platforms.
- Monitoring and troubleshooting data pipelines, identifying and resolving performance issues and bottlenecks.
- Ensuring data security and compliance with data governance policies and regulations.
- Managing data infrastructure on AWS, including capacity planning, cost optimization, and resource allocation.
- Staying up to date with emerging data engineering technologies, trends, and best practices, and evaluating their applicability to improve data systems and processes.
- Documenting data engineering processes, workflows, and solutions for knowledge sharing and future reference.
- Ability and flexibility to coordinate and work with teams distributed across time zones, as needed. For instance, early morning/late evening hours to coordinate with teams in India
- Bachelor's or Master's degree in Computer Science or related engineering field and deep experience with AWS infrastructure
- 5+ years of strong experience in data engineering, specifically with AWS backend tech stack, including but not limited to S3, Redshift, Glue, Lambda, EMR, and Athena.
- 7+ years of proficiency in programming languages commonly used in data engineering, such as Python.
- 3+ years of hands-on experience with big data processing frameworks, such as Apache Spark.
- 5+ years of hands-on experience with data modeling, ETL development, and data integration techniques.
- Working knowledge of relational and dimensional data design and modeling in a large multi-platform data environment
- Solid understanding of SQL and database concepts.
- 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 drive continuous data management quality (i.e. timeliness, 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
- Familiarity with data warehousing principles and best practices.
- Excellent problem solver - use of data and technology to solve problems or answer complex data related questions
- Excellent communication and collaboration skills to work effectively in cross-functional teams.
- 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
McDonald’s is committed to providing qualified individuals with reasonable accommodations to perform the essential functions of their jobs. Additionally, if you (or another applicant of whom you are aware) require assistance accessing or reading this job posting or otherwise seek assistance in the application process, please contact firstname.lastname@example.org
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