This role pays more than
53%
of similar roles. Most pay
$151,000–$223,750
— the shaded band above.
At the midpoint, this role pays about
$198k
versus about
$187k
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
623 open roles
on FindRole.
Listed pay typically runs
$148,300–$222,500
across 603 roles with salary data.
The Data Platform Engineer, Senior Staff joins the Information Technology Group to design, build, and operate a modern data platform centered on Databricks Lakehouse architecture. This high-impact role involves designing scalable distributed systems, managing Databricks workspace governance, and implementing infrastructure as code using Terraform and Terramate. The engineer will develop end-to-end data pipelines for analytics and machine learning, manage Amazon EKS clusters, and establish CI/CD pipelines for various artifacts including SQL and notebooks. Key responsibilities include monitoring SLIs and SLOs, ensuring security compliance in regulated environments, and mentoring team members on platform standards. Required technical skills include proficiency in Python, Bash, Java, and SQL or NoSQL databases. The role focuses on solving complex infrastructure challenges by modernizing legacy systems and optimizing cloud-based data workloads within a sophisticated multi-account environment.
Design and build scalable, distributed data platform systems using Databricks Lakehouse as the core foundation.
Manage Databricks workspace architecture, governance, and lifecycle management including Unity Catalog and Delta Lake.
Implement infrastructure as code using Terraform or Terramate to automate cloud resources.
Build and support end-to-end data pipelines for ingestion, analytics, and machine learning workloads.
Develop and maintain CI/CD pipelines for infrastructure, notebooks, SQL scripts, and ML artifacts.
Operate and optimize Amazon EKS clusters to support large-scale data processing.
Define and monitor SLIs and SLOs to ensure platform reliability and data quality.
Implement security, compliance, and governance controls in accordance with industry standards.
What we're looking for
A Bachelor's degree in Computer Engineering, Computer Science, Information Systems, or a related field is required, or 9+ years of IT experience without a degree.
Candidates must have at least 7 years of IT-related work experience if they hold a relevant degree.
At least 5 years of experience in programming with languages such as Java or Python is required.
At least 3 years of experience with SQL or NoSQL databases and 3 years with data structures and algorithms are required.
Candidates must have at least 8 years of experience building and operating large-scale cloud platforms.
Experience includes 5+ years in Data Platform, DevOps, SRE, or DataOps roles.
Expertise is required in AWS infrastructure, Databricks Lakehouse (Unity Catalog, Delta Lake, MLflow), and Terraform/Terramate for IaC.
Candidates should possess an AWS Certified DevOps Engineer – Professional certification or equivalent experience.
Databricks
Delta Lake
Unity Catalog
AWS
Python
Java
SQL
NoSQL
Data Engineering
Data Modeling
Machine Learning
Data Governance
Fivetran
HVR
Vault
Data Observability
Databricks
Delta Lake
Unity Catalog
AWS
Python
Java
SQL
NoSQL
Data Engineering
Data Modeling
Machine Learning
Data Governance
Fivetran
HVR
Vault
Data Observability
PostgreSQL
DynamoDB
Kafka
Flink
Spark
Delta Lake
Distributed Systems
CDC
Database Sharding
Proxy Architecture
Data Lake
Real-time Streaming
Data Ingestion
Kubernetes
EC2
Caching Systems
PostgreSQL
DynamoDB
Kafka
Flink
Spark
Delta Lake
Distributed Systems
CDC
Data Lake
Caching Systems
Database Sharding
Proxy Architecture
Real-time Streaming
Data Ingestion
Kubernetes
EC2
WarpStream