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Senior Data Engineer

Company Description

McDonald’s growth strategy, Accelerating the Arches, encompasses all aspects of our business as the leading global omni-channel restaurant brand. As the consumer landscape shifts we are using our competitive advantages to further strengthen our brand. One of our core growth strategies is to Double Down on the 3Ds (Delivery, Digital and Drive Thru). McDonald’s will accelerate technology innovation so 65M+ customers a day will experience a fast, easy experience, whether at one of our 25,000 and growing Drive thrus, through McDelivery, dine-in or takeaway. 

McDonald’s Global Technology is here to power tomorrow’s feel-good moments.That’s why you’ll find us at the forefront of transformative technology, exploring new and innovative ways to serve our millions of customers and spread happiness one delicious Hot Fudge Sundae-dipped fry at a time. Using AI, robotics and emerging tech, we’re digitizing the Golden Arches. Combine that with our unparalleled global scale, and we’re reshaping all areas of the business, industry and every community that is home to a McDonald’s restaurant. We face complex tech challenges every day. But that’s where our diverse and talented teams come in. They’re made up of the best and brightest from all over the globe, and they thrive in the space where feel-good meets fast-paced.  

Check out the McDonald’s  Global Technology Technical Blog to learn how technology and our global team are directly enabling the Accelerating the Arches strategy. 

Job Description

McDonald’s Global Technology – Data & Analytics team is looking to hire a Senior 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 Senior Data Engineer, you will collaborate with data scientists, analysts, and other cross-functional teams to ensure the availability, reliability, and performance of data systems. You will take ownership of engineering modules and act as an experienced leader of other engineers. 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.

Responsibilities:

  • 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.
  • Owns engineering modules and functionalities and supports them through a full development cycle
  • Leads a back-end engineering team and facilitates cross-functional relationships to solve relevant business issues
  • 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 integration processes to extract, transform, and load data from various sources into cloud-based data storage solutions 
  • 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 cloud-based platform (i.e. GCP), 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

Benefits eligible: Yes
Bonus eligible: Yes
Long term incentive eligible: Yes
The expected salary range for this role is $149,260 – $190310 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.

Qualifications

  • Bachelor's or Master's degree in Computer Science or related engineering field and deep experience with Google Cloud Platform (GCP) infrastructure
  • 10+ years of strong experience in data engineering, preferably with cloud-based tech stack
  • 7+ years of proficiency in programming languages commonly used in data engineering, such as Python.
  • 5+ years of hands-on experience with big data processing frameworks, such as Apache Spark.
  • 5+ years of hands-on experience with data modeling, ETL / ELT development, and data integration techniques.
  • Experience with RELTIO master data management and integration is a strong plus
  • 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
  • Experience in leading engineering teams in development efforts
  • 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.

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

Additional Information

Benefits eligible: This position offers health and welfare benefits, a 401(k) plan, adoption assistance program, educational assistance program, flexible ways of working, and time off policies (including sick leave, parental leave, and vacation/PTO). Eligibility requirements apply to some benefits and may depend on job classification and length of employment. 

Bonus eligible: This position is eligible for a bonus, calculated based on individual and company performance.

Long term Incentive eligible: This position is eligible for stock or other equity grants pursuant to McDonald’s long-term incentive plan.

McDonald’s is an equal opportunity employer committed to the diversity of our workforce. We promote an inclusive work environment that creates feel-good moments for everyone. McDonald’s provides reasonable accommodations to qualified individuals with disabilities as part of the application or hiring process or to perform the essential functions of their job. If you need assistance accessing or reading this job posting or otherwise feel you need an accommodation during the application or hiring process, please contact [email protected]. Reasonable accommodations will be determined on a case-by-case basis.

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.

Average salary estimate

$169785 / YEARLY (est.)
min
max
$149260K
$190310K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Engineer, McDonald's Corporation

Join the team at McDonald's as a Senior Data Engineer, where your expertise will help shape the future of one of the world's most iconic brands. Located at 110 N Carpenter St, Chicago, IL, you'll be part of the Global Technology – Data & Analytics team, driving innovation and efficiency through scalable and reliable data solutions. In this role, you’ll collaborate closely with data scientists and analysts to ensure that our data systems meet the high standards needed to support our ambitious strategy, Accelerating the Arches. You’ll take ownership of engineering modules, leading your peers, while also delving into exciting projects that range from designing data pipelines to problem-solving data quality issues. With over a decade of experience in data engineering and a solid grasp of cloud computing platforms like Google Cloud Platform (GCP), you’ll play a pivotal role in developing and optimizing data architectures. This isn’t just about data; it's about contributing to a transformative journey, steering high-quality data products, and steering Big Data initiatives that impact millions of customers each day. Plus, you’ll enjoy fostering an inclusive environment where diverse teams come together to tackle complex tech challenges. If you're ready to redefine fast food with your data prowess at a company that services over 65 million customers daily, we want to hear from you!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at McDonald's Corporation
What are the key responsibilities of a Senior Data Engineer at McDonald's?

As a Senior Data Engineer at McDonald's, your primary responsibilities include building and maintaining scalable data products, leading back-end engineering teams, and collaborating with analysts to enhance data integrity. You will design data pipelines, troubleshoot performance issues, and ensure compliance with data governance policies. Leveraging your expertise in Google Cloud Platform (GCP) is crucial as you develop innovative solutions that contribute to the company’s data-driven decision-making.

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What qualifications do I need to apply for the Senior Data Engineer position at McDonald's?

To qualify for the Senior Data Engineer position at McDonald's, candidates should possess a Bachelor’s or Master’s degree in Computer Science or a related field, along with at least 10 years of experience in data engineering. Proficiency in programming languages such as Python, experience with big data frameworks like Apache Spark, and a thorough knowledge of SQL are essential. Additionally, leadership experience in engineering projects and familiarity with data governance practices will strengthen your application.

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What technologies are primarily used by Senior Data Engineers at McDonald's?

Senior Data Engineers at McDonald's predominantly utilize the Google Cloud Platform (GCP) for data storage and management. Expertise in programming languages like Python and familiarity with big data processing frameworks such as Apache Spark are critical. Experience with relational data frameworks and master data management tools is also beneficial, as some responsibilities include building and optimizing data integration workflows across platforms.

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What kind of team dynamics can a Senior Data Engineer expect at McDonald's?

At McDonald's, Senior Data Engineers work within diverse, cross-functional teams composed of data scientists and analysts. The culture emphasizes collaboration and innovative problem-solving. You'll lead by example, owning engineering modules and facilitating teamwork across different time zones, fostering an environment where fresh ideas and backgrounds contribute to finding solutions to complex tech challenges.

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How does McDonald's support professional growth for Senior Data Engineers?

McDonald's is committed to the continuous professional growth of its employees, particularly for roles like Senior Data Engineer. They provide access to training programs, encourage knowledge sharing through documentation and collaboration, and foster a culture of innovation that allows individuals to keep up with emerging technologies and best practices in data engineering.

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Common Interview Questions for Senior Data Engineer
Can you describe your experience with data modeling and ETL development as a Senior Data Engineer?

When answering this question, highlight specific projects where you applied data modeling techniques and performed ETL development. Discuss your approach to designing data models, managing data flows, and ensuring data quality throughout the ETL process. Provide examples of frameworks you've used and any challenges faced, emphasizing how you collaborated with cross-functional teams to deliver effective solutions.

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How do you ensure data quality and integrity in your work?

Discuss your familiarity with data governance principles and the processes you employ to maintain accuracy and reliability in data systems. Detail your experience with data cleansing, standardization, and validation techniques. It's beneficial to mention any specific tools you've utilized for monitoring data quality and the importance of defining clear business rules to govern data usage.

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What strategies do you use to optimize data pipelines for performance?

Describe the techniques you implement for optimizing data pipelines, such as parallel processing or efficient resource allocation in cloud environments. Share specific examples of performance bottlenecks you encountered and how you resolved them, including any tools for monitoring pipeline efficiency.

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How do you handle data security and compliance in your engineering practices?

This is an opportunity to emphasize your understanding of data security protocols and compliance regulations. Discuss how you identify potential security risks and implement best practices to mitigate them. Mention experiences related to managing sensitive data and compliance with industry standards, helping demonstrate your approach to safeguarding data integrity.

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What is your experience with leading engineering teams?

Provide examples of how you've successfully led engineering teams in previous roles, focusing on project workflows, team dynamics, and conflict resolution. Illustrate your leadership style, how you encourage collaboration, and the impact your guidance had on project outcomes.

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Can you explain a complex technical concept to a non-technical audience?

Employ simple analogies or examples that can help clarify the concept. This question tests not only your understanding of the subject but also your ability to communicate effectively. Share your experience of simplifying intricate data engineering topics for stakeholders or colleagues, contributing to better decision-making.

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How do you stay updated with emerging data engineering technologies?

Talk about your commitment to professional development, whether through attending webinars, engaging in online courses, following tech blogs, or participating in relevant forums. Highlight specific technologies you are interested in, and how you evaluate their potential applicability to your work at McDonald's.

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What challenges have you faced in data integration projects, and how did you overcome them?

Identify specific integration challenges you’ve encountered, such as data format discrepancies or synchronization issues. Discuss your problem-solving strategies, collaboration with other teams, and the eventual successful resolution that improved data workflows.

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How do you balance multiple projects and priorities in your role as a Senior Data Engineer?

Share your time management strategies, whether through project management tools, prioritization techniques, or regular check-ins with stakeholders. Discuss how you remain adaptable to changing project scopes and timelines, ensuring timely delivery of high-quality work.

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What methods do you use for documenting data engineering processes?

Explain your approach to documenting workflows and solutions, emphasizing clarity and accessibility. Mention any tools you've utilized, like Confluence or JIRA, and discuss why documentation is crucial for knowledge sharing and maintaining a culture of continuous improvement in data engineering practices.

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McDonald's Corporation is a chain of fast food restaurants. Headquartered in Oak Brook, Illinois, the company's famous menu items include the Big Mac, Chicken McNuggets and Egg McMuffin. McDonald's is a publicly owned company and operates a Canadi...

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March 20, 2025

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