Data Engineer Jobs at Qualcomm with Visa Sponsorship
Data Engineer jobs at Qualcomm sit at the intersection of semiconductor innovation and large-scale data infrastructure, supporting everything from chip telemetry pipelines to media platform analytics. Qualcomm has a consistent track record of sponsoring international candidates for engineering functions, making it a realistic target if you're on a work visa.
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Qualcomm Incorporated
Job Area:
Information Technology Group, Information Technology Group > IT Software Developer
General Summary:
The Staff Data Engineer / Full‑Stack Data Developer is a senior, hands‑on individual contributor responsible for designing, building, optimizing, and operating data pipelines, curated data products, and Databricks‑native data applications on a modern cloud Lakehouse platform. This role is critical to enabling enterprise analytics, BI, AI/ML, and data‑driven applications, with deep expertise in Databricks, Python, Spark, and Databricks application development.
This position requires strong end‑to‑end ownership of data engineering and data app solutions, production‑grade engineering rigor, and the ability to collaborate across platform, analytics, and application teams.
This role requires full-time onsite work in San Diego, CA (5 days per week).
Minimum Qualifications:
- 5+ years of IT-related work experience with a Bachelor's degree in Computer Engineering, Computer Science, Information Systems or a related field.
OR
- 7+ years of IT-related work experience without a Bachelor’s degree.
- 3+ years of work experience with programming (e.g., Java, Python).
- 3+ years of work experience with SQL or NoSQL Databases.
- 3+ years of work experience with Data Structures and algorithms.
Key Responsibilities
Data Engineering & Development
- Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and Python to support enterprise analytics, AI, and application use cases.
- Build and manage curated data layers following Lakehouse Medallion architecture best practices (Bronze / Silver / Gold).
- Develop reusable, modular data transformation frameworks to accelerate delivery across domains.
Databricks Application Development
- Design and develop Databricks‑native data applications, including notebook‑based apps, Databricks dashboards, and interactive data experiences for analytics and business users.
- Build data APIs, parameterized pipelines, and app‑integrated data services leveraging Databricks and Lakehouse capabilities.
- Partner with analytics, AI, and application teams to embed data and insights directly into workflows and applications.
- Ensure Databricks apps meet performance, security, governance, and usability standards.
Performance, Scalability & Reliability
- Optimize Apache Spark jobs and Databricks workloads for performance, cost efficiency, scalability, and reliability.
- Proactively address challenges related to data volume, schema evolution, and compute optimization.
- Implement robust data quality checks, validations, and anomaly detection within pipelines and apps.
Production Support & Operations
- Own and support production data pipelines and Databricks applications, including monitoring, troubleshooting, and root‑cause analysis.
- Ensure high availability, data correctness, and SLA adherence for business‑critical datasets and apps.
- Contribute to observability, alerting, and operational automation.
Full‑Stack Data Enablement
- Collaborate with BI, analytics, AI/ML, platform, and application teams to deliver end‑to‑end data solutions.
- Enable data consumption across dashboards, reports, Databricks apps, AI models, APIs, and downstream applications.
- Translate business and analytical requirements into well‑designed data pipelines and data applications.
Engineering Excellence & Technical Influence
- Act as a technical leader and mentor, defining best practices for data engineering and Databricks app development.
- Participate in architecture reviews, design discussions, and technical roadmaps.
- Continuously evaluate and adopt modern Databricks features, GenAI capabilities, and automation patterns to improve developer productivity.
Required Skills & Experience
- 5+ years of hands‑on data engineering experience, owning production‑grade pipelines and data solutions.
- Strong proficiency in Python and Apache Spark (PySpark).
- Proven hands‑on experience working with Databricks in production, including Databricks application development.
- Strong SQL and data transformation skills.
- Experience building and supporting Databricks notebooks, dashboards, and data‑driven applications.
- Experience operating and supporting data pipelines and data apps in production environments.
- Solid understanding of data quality, reliability, security, and governance.
Preferred / Nice‑to‑Have Qualifications
- Experience with AWS cloud services (e.g., S3, IAM, EC2, Glue, or equivalent).
- Exposure to Unity Catalog, access controls, metadata management, and governed data sharing.
- Experience with streaming data pipelines (e.g., Structured Streaming, Kafka).
- Familiarity with CI/CD, Git‑based workflows, and Data/Analytics DevOps.
- Experience enabling BI, AI/ML, or application‑embedded analytics using Databricks.
What Defines Success at the Staff Level
- Owns complex data pipelines and Databricks applications end‑to‑end with minimal oversight.
- Drives improvements in performance, reliability, cost efficiency, and usability across data and app layers.
- Influences architecture, standards, and best practices beyond immediate assignments.
- Serves as a trusted technical partner to analytics, AI, platform, and application teams.
Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
Pay range and Other Compensation & Benefits:
$128,100.00 - $192,100.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link.
If you would like more information about this role, please contact Qualcomm Careers.
Company:
Qualcomm Incorporated
Job Area:
Information Technology Group, Information Technology Group > IT Software Developer
General Summary:
The Staff Data Engineer / Full‑Stack Data Developer is a senior, hands‑on individual contributor responsible for designing, building, optimizing, and operating data pipelines, curated data products, and Databricks‑native data applications on a modern cloud Lakehouse platform. This role is critical to enabling enterprise analytics, BI, AI/ML, and data‑driven applications, with deep expertise in Databricks, Python, Spark, and Databricks application development.
This position requires strong end‑to‑end ownership of data engineering and data app solutions, production‑grade engineering rigor, and the ability to collaborate across platform, analytics, and application teams.
This role requires full-time onsite work in San Diego, CA (5 days per week).
Minimum Qualifications:
- 5+ years of IT-related work experience with a Bachelor's degree in Computer Engineering, Computer Science, Information Systems or a related field.
OR
- 7+ years of IT-related work experience without a Bachelor’s degree.
- 3+ years of work experience with programming (e.g., Java, Python).
- 3+ years of work experience with SQL or NoSQL Databases.
- 3+ years of work experience with Data Structures and algorithms.
Key Responsibilities
Data Engineering & Development
- Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and Python to support enterprise analytics, AI, and application use cases.
- Build and manage curated data layers following Lakehouse Medallion architecture best practices (Bronze / Silver / Gold).
- Develop reusable, modular data transformation frameworks to accelerate delivery across domains.
Databricks Application Development
- Design and develop Databricks‑native data applications, including notebook‑based apps, Databricks dashboards, and interactive data experiences for analytics and business users.
- Build data APIs, parameterized pipelines, and app‑integrated data services leveraging Databricks and Lakehouse capabilities.
- Partner with analytics, AI, and application teams to embed data and insights directly into workflows and applications.
- Ensure Databricks apps meet performance, security, governance, and usability standards.
Performance, Scalability & Reliability
- Optimize Apache Spark jobs and Databricks workloads for performance, cost efficiency, scalability, and reliability.
- Proactively address challenges related to data volume, schema evolution, and compute optimization.
- Implement robust data quality checks, validations, and anomaly detection within pipelines and apps.
Production Support & Operations
- Own and support production data pipelines and Databricks applications, including monitoring, troubleshooting, and root‑cause analysis.
- Ensure high availability, data correctness, and SLA adherence for business‑critical datasets and apps.
- Contribute to observability, alerting, and operational automation.
Full‑Stack Data Enablement
- Collaborate with BI, analytics, AI/ML, platform, and application teams to deliver end‑to‑end data solutions.
- Enable data consumption across dashboards, reports, Databricks apps, AI models, APIs, and downstream applications.
- Translate business and analytical requirements into well‑designed data pipelines and data applications.
Engineering Excellence & Technical Influence
- Act as a technical leader and mentor, defining best practices for data engineering and Databricks app development.
- Participate in architecture reviews, design discussions, and technical roadmaps.
- Continuously evaluate and adopt modern Databricks features, GenAI capabilities, and automation patterns to improve developer productivity.
Required Skills & Experience
- 5+ years of hands‑on data engineering experience, owning production‑grade pipelines and data solutions.
- Strong proficiency in Python and Apache Spark (PySpark).
- Proven hands‑on experience working with Databricks in production, including Databricks application development.
- Strong SQL and data transformation skills.
- Experience building and supporting Databricks notebooks, dashboards, and data‑driven applications.
- Experience operating and supporting data pipelines and data apps in production environments.
- Solid understanding of data quality, reliability, security, and governance.
Preferred / Nice‑to‑Have Qualifications
- Experience with AWS cloud services (e.g., S3, IAM, EC2, Glue, or equivalent).
- Exposure to Unity Catalog, access controls, metadata management, and governed data sharing.
- Experience with streaming data pipelines (e.g., Structured Streaming, Kafka).
- Familiarity with CI/CD, Git‑based workflows, and Data/Analytics DevOps.
- Experience enabling BI, AI/ML, or application‑embedded analytics using Databricks.
What Defines Success at the Staff Level
- Owns complex data pipelines and Databricks applications end‑to‑end with minimal oversight.
- Drives improvements in performance, reliability, cost efficiency, and usability across data and app layers.
- Influences architecture, standards, and best practices beyond immediate assignments.
- Serves as a trusted technical partner to analytics, AI, platform, and application teams.
Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
Pay range and Other Compensation & Benefits:
$128,100.00 - $192,100.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link.
If you would like more information about this role, please contact Qualcomm Careers.
See all Data Engineer Jobs at Qualcomm
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Engineer Jobs at Qualcomm.
Get Access To All JobsTips for Finding Data Engineer Jobs at Qualcomm
Align your portfolio to Qualcomm's data stack
Qualcomm's Data Engineer roles frequently involve distributed systems, telemetry pipelines, and large-scale ETL at the chip and platform layer. Showcase projects in Spark, Kafka, or cloud-native data warehousing before you apply, not after.
Time your OPT application before your start date
If you're on F-1, USCIS recommends filing your OPT EAD application up to 90 days before your program end date. Qualcomm's onboarding timelines are fixed, so a delayed EAD can cost you the offer.
Target Qualcomm's media analytics and platform teams
Within Media and Entertainment, Qualcomm staffs Data Engineers on content delivery, streaming quality, and audience analytics pipelines. Applying to these specific teams positions you for roles where the data scope and sponsorship pathway are both well established.
Understand how Qualcomm handles H-1B transfers
If you're already on an H-1B with another employer, Qualcomm can file an H-1B transfer petition, letting you start work as soon as USCIS receives it. Get your current I-94 and approval notice ready before your recruiter screens you.
Use Migrate Mate to filter open Data Engineer roles by visa type
Searching broadly across job boards buries sponsorship-friendly postings. Use Migrate Mate to filter Qualcomm's Data Engineer openings by the visa types they actively sponsor, so you're only applying where your status is already a fit.
Prepare for PERM early if you're targeting long-term residency
Qualcomm sponsors Green Card petitions through PERM for senior engineering hires, and the DOL audit process can add 12 to 18 months to the timeline. Raise your long-term status goals with your recruiter during the offer stage, not after you've signed.
Frequently Asked Questions
Does Qualcomm sponsor H-1B visas for Data Engineers?
Yes, Qualcomm sponsors H-1B visas for Data Engineer roles. Engineering functions, including data infrastructure and analytics, are among the positions where Qualcomm has a consistent pattern of sponsorship. If you're in the H-1B lottery pool or seeking a transfer from an existing H-1B visa, Qualcomm's recruiting team is familiar with both paths.
How do I apply for Data Engineer jobs at Qualcomm?
You can browse and apply directly through Qualcomm's careers portal, or use Migrate Mate to filter Data Engineer openings at Qualcomm by the visa types they sponsor. Tailor your resume to reflect large-scale data pipeline experience, distributed systems, and any domain knowledge relevant to Qualcomm's media or semiconductor analytics teams before submitting.
Which visa types does Qualcomm commonly sponsor for Data Engineer roles?
Qualcomm sponsors several visa categories for Data Engineer positions, including H-1B, H-1B1 visa, TN visa for Canadian and Mexican nationals, F-1 OPT and CPT for students completing U.S. degrees, J-1 visa for qualifying exchange visitors, and EB-2 or EB-3 Green Card pathways for longer-term hires. The visa type pursued typically depends on your nationality, degree level, and where you are in your career.
What qualifications does Qualcomm expect for Data Engineer roles?
Qualcomm's Data Engineer postings typically require a bachelor's or master's degree in Computer Science, Electrical Engineering, or a closely related field. Hands-on experience with distributed data systems, cloud platforms such as AWS or GCP, and pipeline tooling like Apache Spark or Kafka is consistently expected. For H-1B sponsorship, the role must qualify as a specialty occupation, which a relevant technical degree generally satisfies.
How do I plan my timeline if Qualcomm offers me a Data Engineer role with H-1B sponsorship?
If you're outside the U.S. or on OPT, the H-1B cap-subject filing window opens April 1 each year, with a lottery registration period in March. USCIS standard processing takes three to five months after filing; premium processing cuts that to 15 business days. Work backwards from your intended start date and discuss the filing plan with Qualcomm's immigration team as soon as you receive an offer.