below marketmost similar roles pay hereabove market
This role pays less than
78%
of similar roles. Most pay
$149,500–$223,750
— the blue band above.
At the midpoint, this role pays about
$144k
versus about
$187k
for comparable roles.
Based on 240 similar postings.
Employer
About Amd
AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors
Amd currently has
496 open roles
on FindRole.
Listed pay typically runs
$172,000–$258,000
across 496 roles with salary data.
The Staff Data Engineer joins the Marketing Analytics team to build and operationalize a data foundation supporting advanced analytics, data science, and machine learning. This role involves leading the hands-on development of scalable data pipelines, canonical data models, and reusable datasets for use cases like lead scoring, attribution, and campaign optimization. You will integrate internal and external data via APIs into environments like Snowflake or Databricks, establishing workflows, quality controls, and documentation for repeatable model development. Key technical requirements include proficiency in SQL, Python, and Spark or PySpark, alongside experience with dbt, Airflow, and MLOps practices. You will translate marketing requirements into engineering solutions, managing complex data from CRM, marketing automation, and digital analytics to solve problems related to historical tracking, entity resolution, and point-in-time logic.
What does a Data Engineer earn?
Median $159000 from 203 postings across 58 companies.
Build and operate scalable marketing data pipelines within Snowflake or Databricks to create analysis-ready datasets.
Develop reusable API integrations and ingestion frameworks for CRM, marketing automation, and digital analytics data.
Design and maintain canonical datasets and shared data models with consistent definitions for core marketing entities.
Engineer specific datasets for machine learning, including feature engineering, label generation, and point-in-time logic.
Establish data quality, observability, and operational reliability through automated validation and pipeline monitoring.
Translate business requirements from marketing and data science stakeholders into technical engineering specifications.
Lead hands-on engineering delivery by reviewing technical designs, mentoring engineers, and improving development practices.
What we're looking for
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical field.
Master’s degree or equivalent advanced experience (preferred).
Experience in data engineering, analytics engineering, data platform development, or a related discipline, including leading technical projects or small engineering teams (preferred).
Strong hands-on proficiency in SQL and Python for developing production-grade data pipelines and transformations (preferred).
Hands-on experience with Snowflake, Databricks, or comparable cloud data platforms, including data modeling and workload optimization (preferred).
Experience building API-based data integrations and preparing data for machine learning and data science workflows (preferred).
Familiarity with MLOps, workflow orchestration, Git-based version control, and tools such as dbt or Airflow (preferred).
Experience designing canonical data models and understanding marketing and sales data ecosystems (preferred).