Data Engineer III

McDonald’s Corporation

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Chicago, IL
Salary
$138,207–$172,758 / yr
Posted
1 day ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $158k
This role $155k
$107k $197k
below market most similar roles pay here above market

This role pays more than 60% of similar roles. Most pay $126,800–$188,350 — the blue band above. At the midpoint, this role pays about $155k versus about $158k for comparable roles.

Based on 240 similar postings.

Employer

About McDonald’s Corporation

McDonald’s Corporation is the world's largest fast-food chain by revenue, operating over 40,000 locations in more than 100 countries.

McDonald’s Corporation currently has 23 open roles on FindRole.

Listed pay typically runs $138,207–$172,758 across 22 roles with salary data.

Most-posted roles

View all roles at McDonald’s Corporation

At a glance

TL;DR · Data Engineer III

The Data Engineer III joins the Global Technology Data & Analytics team to build scalable, efficient data solutions supporting various analytics initiatives. This role involves designing and developing data pipelines and ETL processes to extract, transform, and load data from diverse sources into cloud storage. Key responsibilities include maintaining reliable data products, implementing scalable architectures, and optimizing integration workflows for real-time processing. The candidate will utilize a technical stack including GCP and AWS technologies such as GCS, BigQuery, S3, Redshift, Cloud Functions, Cloud Run, Glue, and Lambda. Proficiency in Python, SQL, Apache Spark, and Apache Kafka is required. The role focuses on solving complex business problems through data modeling, ensuring data quality, security, and governance across a large multi-platform data environment.

What does a Data Engineer earn?

Median $162000 from 206 postings across 61 companies.

See salary data

What you'll do

  • Design and develop data pipelines and ETL processes to move data into cloud storage solutions.
  • Build and maintain reliable data products that support specific business needs and analytics initiatives.
  • Implement and maintain scalable data architectures for efficient storage, retrieval, and processing.
  • Build and optimize data integration workflows for real-time and near real-time data streaming.
  • Monitor and troubleshoot data pipelines to identify and resolve performance issues or bottlenecks.
  • Manage cloud data infrastructure including capacity planning, cost optimization, and resource allocation.
  • Ensure data security and compliance with established data governance policies and regulations.
  • Document data engineering processes, workflows, and solutions for knowledge sharing and future reference.

What we're looking for

  • Bachelor's or Master's degree in Computer Science or a related engineering field.
  • Deep experience with cloud infrastructure and backend tech stacks including GCP and AWS.
  • Deep hands-on experience in data engineering with tools like GCS, BigQuery, S3, Redshift, Glue, and Lambda.
  • Proficiency in programming languages commonly used in data engineering, such as Python.
  • Hands-on experience with big data processing frameworks like Apache Spark.
  • Hands-on experience with real-time data streaming using Apache Kafka, Spark Structured Streaming, Apache Beam, Google Cloud Dataflow, or Flink.
  • Proficiency in SQL with a good understanding of database concepts.
  • Experience with JIRA and Confluence as part of project workflow and documentation tools (preferred).
  • Experience with Agile project management methods and terminology (preferred).

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