Data Engineer

Company Description:

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.

Job Description:

McDonald’s is seeking a skilled Data Engineer with a strong background in data driven platforms.  As an integral member of Data Architecture team, you will be responsible for the design, development, and deployment of advanced scalable data pipelines.  In this role you will collaborate with data architects, solution architects, analysts, and data scientists.  Your commitment to data integrity, combined with a passion for pioneering innovative data engineering strategies, will be essential for driving our data initiatives forward.

Responsibilities:

• Collaborating with data scientists and analysts to understand data requirements and ensure data accuracy, integrity, and availability. 
• Build and maintain robust and performant data pipelines for structured and unstructured data integration utilizing AWS cloud native services (e.g., Glue, Lambda, Redshift, RDS) and other data analytics platforms like Databricks and Snowflake.  
• Provide monitoring recommendations for data quality and completeness, ensuring production data is always accurate and available for quick and efficient querying.
• Monitor data pipeline performance by defining relevant metrics to provide alerting and performance insights.
• Monitoring and troubleshooting data pipelines, identifying, and resolving performance issues and scalability. 
• Re-evaluate existing processes and tools, recommending and implementing improvements.
• Adopt and establish best practices in data engineering, and guide product data engineering teams to ensure adherence to these standards.
• Provide comprehensive documentation on design decisions, data flows, source-to-target-mappings, and input into data interface contracts.
• Continuously monitor the latest developments in data engineering, assessing their potential to improve and elevate our systems and procedures.
• Develops a solid understanding of the technical details of data domains, and clearly understands what business problems are being solved.
• Ensuring data security and compliance with data governance policies and regulations. 

Qualifications:

• Bachelor's degree in information technology, or a related field.
• 5+ years of data engineering experience designing, building, and deploying batch and real-time data pipelines utilizing AWS managed services - S3, Glue Lambda, EMR, EKS, MSK, and Redshift.
• 5+ years coding experience with Python, Spark, and advance SQL.
• 5+ years of experience with database technologies like AWS Redshift, Snowflake, Databricks, or GCP BigQuery.
• 2+ years of experience building data pipelines for SAS analytics.
• 2+ years of experience using Talend, Informatic Power Center, or similar ETL tool.
• 5+ years of experience with cloud services like AWS, AZURE, or GCP - AWS preferred.
• Experience with JIRA and Confluence a plus.
• AWS Data Engineer certification.

Preferred Skills:

• Ability to make appropriate data engineering design and tools selection recommendations based on project requirements and best practices.
• Follow data management and data governance defined principles (i.e., completeness, accuracy, lineage).
• Ability to perform extensive data analysis (comparing multiple datasets) using a variety of tools.
• Excellent problem solver - use of data and technology to solve problems or answer complex data related questions.
• Strong communication and collaboration skills to work effectively in cross-functional teams.
• Experience working in an environment using an agile project management methodology.
• Excellent written, verbal, and meeting facilitation skills.
• Self-driven with ability to set priorities and mentor others in a performance driven environment.

Additional Information:

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 recruiting.supportteam@us.mcd.com

McDonald’s provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to sex, sex stereotyping, pregnancy (including pregnancy, childbirth, and medical conditions related to pregnancy, childbirth, or breastfeeding), race, color, religion, ancestry or national origin, age, disability status, medical condition, marital status, sexual orientation, gender, gender identity, gender expression, transgender status, protected military or veteran status, citizenship status, genetic information, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Nothing in this job posting or description should be construed as an offer or guarantee of employment.