below marketmost similar roles pay hereabove market
This role pays less than
62%
of similar roles. Most pay
$135,456–$223,750
— the blue band above.
At the midpoint, this role pays about
$162k
versus about
$180k
for comparable roles.
Based on 240 similar postings.
Employer
About Qualcomm
Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.
Qualcomm currently has
575 open roles
on FindRole.
Listed pay typically runs
$147,900–$221,900
across 550 roles with salary data.
The Staff Data Engineer / Full‑Stack Data Developer is a senior individual contributor within the Information Technology Group. This role involves designing, building, and operating data pipelines, curated data products, and Databricks-native applications on a modern cloud Lakehouse platform. You will develop scalable ETL/ELT pipelines, manage curated data layers using Medallion architecture, and build interactive data experiences like notebooks and dashboards. Key responsibilities include optimizing Apache Spark jobs for performance and cost efficiency while ensuring data quality and security. You will utilize Python, PySpark, SQL, and NoSQL databases to support enterprise analytics, AI, and ML use cases. The position requires translating business requirements into production-grade engineering solutions, providing technical leadership, and managing end-to-end data lifecycle operations to enable data-driven applications across the organization.
Design and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and Python.
Build curated data layers following Lakehouse Medallion architecture best practices.
Develop Databricks-native applications including notebooks, dashboards, and interactive data experiences.
Build data APIs and parameterized pipelines to integrate data services into business workflows.
Optimize Apache Spark jobs for performance, cost efficiency, and reliability.
Implement data quality checks, validations, and anomaly detection within production pipelines.
Monitor and troubleshoot production data pipelines to ensure high availability and SLA adherence.
Define best practices and provide technical leadership for data engineering and Databricks development.
What we're looking for
Must have 5+ years of IT-related work experience with a Bachelor's degree in Computer Engineering, Computer Science, Information Systems, or a related field.
Must have 7+ years of IT-related work experience if a Bachelor's degree is not held.
Must have 3+ years of work experience with programming languages such as Java or Python.
Must have 3+ years of work experience with SQL or NoSQL Databases.
Must have 3+ years of work experience with Data Structures and algorithms.
Must have 5+ years of hands-on data engineering experience owning production-grade pipelines and data solutions.
Must have strong proficiency in Python, Apache Spark (PySpark), and Databricks application development.
Experience with AWS cloud services, Unity Catalog, streaming data pipelines, and CI/CD workflows (preferred).