Manager, Data Engineering

Department Overview

McDonald’s is hiring a Data Engineer III, focused on Digital Payments data ingestion, curation and analytics.  This area covers data flowing from our payment providers and McDonald's payment services. This role sits within Data Analytics, Architecture and AI. This group manages data from various areas of the business, including Sales, Restaurant, Finance and People, and many more. You will work alongside passionate data engineering professionals and business stakeholders focused on Digital Payments, Treasury and MarTech. 

Duties

Primary Responsibilities:

• Builds and maintains relevant and reliable products that support Digital Payments across the organization. Develops and implements new technology solutions as needed to ensure ongoing improvement with data reliability and observability as the key output.
• Participates in new software development engineering and Lead data engineering initiatives, ensuring timely and accurate delivery of products.
• Work closely with the Product owner and help to define business rules that determines the quality of relevant datasets.
• Drive and implement best practices for pipeline development, data governance, data security and quality across the data landscape.
• Ensure scalability, maintainability, and quality of data systems powering payment and marketing decisions.
• Staying up to date with emerging data engineering technologies, trends, and best practices, and evaluating their applicability to meet evolving analytics needs.
• Document data engineering processes, workflows, and solutions for knowledge sharing and future reference. 
• Mentor and coach junior data engineers on best practices using on-the-job experiences.

Ability and flexibility to coordinate and work with teams distributed across time zones, as needed.

Qualifications

Skills Required:

Cloud Technologies (Preferably GCP, BigQuery) , Python, Java, Bash, Airflow, Kafka, Confluent, Spark, DBT, Tableau , Data Pipeline Development (Batch & Streaming), ETL / ELT Design Patterns, ETL Testing, Pipeline, Testing, Github, Jenkins, Git, Maven, Gradle, API Testing

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, with strong hands-on experience in cloud computing platforms such as AWS and GCP.
• 5+ years of professional experience in data engineering, data platform development, or related fields.
• Strong proficiency in Python, Java, or Scala for building scalable data pipelines, automation, and data processing solutions.
• Hands-on experience with data orchestration tools such as Apache Airflow and modern data transformation frameworks like dbt (Data Build Tool).
• Solid experience working with cloud data warehousing solutions including Amazon Redshift and Google BigQuery, with a deep understanding of performance optimization, partitioning, and cost management.
• Experience working with big data ecosystems (e.g., Hadoop, Spark, NoSQL) and distributed data processing frameworks.
• Hands-on experience with BI and data visualization tools such as Tableau, including developing dashboards, optimizing performance, and enabling self-service analytics for business users.
• Strong understanding of data modeling and semantic layer design to support efficient reporting and visualization in BI tools like Tableau
• Strong expertise in data quality and data management functions, including cleansing, standardization, parsing, de-duplication, mapping, and hierarchy management.
• Deep understanding of data product lifecycle, data modeling standards, and engineering best practices in modern data platforms.
• Ability to perform advanced data analysis and reconciliation across multiple datasets using SQL and analytical tools.
• Proven ability to lead technical initiatives, mentor team members, and drive engineering best practices across multiple workstreams.
• Strong communication and stakeholder management skills, with the ability to drive alignment and adoption of data engineering and BI standards.
• Demonstrated experience in data governance, metadata management, and data security frameworks.
• Strong understanding of data warehousing principles, including dimensional modeling, medallion architecture, and ELT design patterns.
• Excellent problem-solving skills with the ability to leverage data and technology to address complex business challenges.
• Excellent verbal and written communication abilities
•  Experience in agile/scrum environments with rapid delivery cycles

Compensation

Bonus Eligible: EDIT

Long - Term Incentive: EDIT

Benefits Eligible: EDIT

Salary Range

The expected salary range for this role is ₹2,924,550.00 - ₹4,021,250.00 per year
 
The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we may also consider your experience, and other job-related factors.