Data Engineer III

McDonald's Corporation•Chicago, IL

50d•$138,207 - $172,758

About The Position

McDonald's is creating smarter, more responsive digital and data systems that transform operations and elevate guest experiences. The Enterprise Data, Analytics, and AI (EDAA) organization empowers every function — Marketing, Operations, Supply Chain, Finance, and more — through seamless integration of business and technology. McDonald's is hiring a Data Engineer III focused on Data Clean Room data ingestion, curation, and analytics. This role sits within Product Engineering & Delivery under Data Clean rooms team and reporting into the Senior Manager, Data Clean Rooms. This group manages data supporting Paid Media measurement, audience activation, attribution, sales lift, and downstream audience use-cases across markets. You will work alongside passionate data engineering professionals, architects, product managers, and business stakeholders focused on Marketing, MarTech, and Commerce Media.

Requirements

Bachelor's or Master's degree in Computer Science or related engineering field and deep experience with Cloud computing.
5+ years of professional experience in data engineering or related fields.
Proficiency in Python and SQL for data processing and automation.
Hands-on experience with data orchestration tools (e.g., Apache Airflow, dbt) and big data ecosystems (e.g., Spark, NoSQL, BigQuery, Snowflake, Databricks).
Expert knowledge of Data Quality functions like cleansing, standardization, parsing, de-duplication, mapping, and hierarchy management.
Deep understanding of Data Product Lifecycle, Standards, and Practices.
Marketing and Marketing Technologies: Working knowledge of the modern MarTech stack — CDPs (mCDP or equivalent), DSPs, DMPs, ad servers, measurement platforms, identity resolution, and consent/privacy platforms.
Clean Rooms and Commerce Media Networks: Hands-on experience with at least one clean room platform (e.g. LiveRamp, Habu, Snowflake Clean Rooms, AWS Clean Rooms, Google Ads Data Hub, or Amazon Marketing Cloud) and familiarity with commerce media / retail media network patterns.
Understanding of privacy-safe data collaboration concepts: hashing, identity graphs, differential privacy, aggregation thresholds, and clean room query patterns.
Ability to perform extensive data analysis (comparing multiple datasets) using a variety of tools.
Familiarity with data warehousing principles and best practices.
Excellent collaboration skills to work effectively in cross-functional teams.

Responsibilities

Builds and maintains relevant and reliable data products that support Data Clean Room generation flows, outbound audience activation pipelines, and downstream consumers of data clean room segments.
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 leads data engineering initiatives, ensuring timely and accurate delivery of DCR products across GCP (prj-cp-dacleanroom-dev01 and related tenants), AWS S3, and LiveRamp Connect.
Works closely with the Product Owner and Data Architects to define business rules that determine the quality of relevant datasets.
Drives and implements best practices for pipeline development, data governance, data security, and quality across the marketing data landscape — including privacy-safe transformations, hashing, and consent enforcement.
Stays up to date with emerging data engineering, MarTech, and clean room technologies, trends, and best practices, and evaluates their applicability to meet evolving analytics needs.
Documents data engineering processes, workflows, and solutions in for knowledge sharing and future reference.
Mentors and coaches junior data engineers and ensures data engineering best-practices.
Ability and flexibility to coordinate and work with teams distributed across time zones (US, EU, IN, APAC), as needed.