Data Analytics Engineer Jobs at Qualcomm with Visa Sponsorship
Data Analytics Engineer jobs at Qualcomm span product lines across mobile, automotive, and connected devices. The company has a consistent track record of sponsoring international engineers in data roles, supporting candidates through H-1B visa, OPT, and Green Card pathways from early hiring stages.
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Get Access To All JobsCompany:
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 Analytics Engineer Jobs at Qualcomm
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Analytics Engineer Jobs at Qualcomm.
Get Access To All JobsTips for Finding Data Analytics Engineer Jobs at Qualcomm
Align your portfolio to Qualcomm's data stack
Qualcomm's analytics roles frequently involve large-scale pipeline work, SQL optimization, and Python or Spark-based modeling. Build out portfolio projects that demonstrate experience with distributed data systems and product analytics, not just dashboard tooling.
Clarify your OPT timeline before applying
If you're on F-1 OPT, confirm your STEM extension eligibility before your first interview. Qualcomm uses E-Verify, which is required to authorize STEM OPT employment, so having your extension timeline clearly mapped reduces friction during offer negotiations.
Target business units with recurring analytics hiring
Qualcomm's semiconductor and connected devices divisions post data analytics roles more consistently than others. Filtering by business unit, not just job title, helps you identify teams that sponsor regularly and have established onboarding workflows for international hires.
Raise sponsorship intent early in recruiter screens
Qualcomm recruiters handle high application volumes across technical roles. Stating your visa status and sponsorship need in the first recruiter call, rather than waiting for the offer stage, prevents wasted interview rounds and signals that you understand the H-1B petition process.
Use Migrate Mate to filter verified sponsoring roles
Qualcomm posts data analytics openings across multiple job boards, but not all reflect active sponsorship intent. Use Migrate Mate to surface roles at Qualcomm verified through DOL Labor Condition Application filings, so you're targeting positions with a real sponsorship history.
Prepare for PERM requirements at the Green Card stage
If Qualcomm moves you toward an EB-2 or EB-3 Green Card, the PERM labor certification requires demonstrating that no qualified U.S. worker was available. Keep documentation of your specialized skills and any unique qualifications that differentiate your candidacy throughout the process.
Frequently Asked Questions
Does Qualcomm sponsor H-1B visas for Data Analytics Engineers?
Yes, Qualcomm sponsors H-1B visas for Data Analytics Engineers and has a documented history of filing petitions through the annual USCIS lottery. Because H-1B selection is subject to the annual cap and lottery, Qualcomm typically initiates the process well ahead of the April filing window. Candidates already on F-1 OPT or STEM OPT are often prioritized since they can begin work before H-1B status takes effect on October 1.
How do I apply for Data Analytics Engineer jobs at Qualcomm?
Applications go through Qualcomm's careers portal, where you can filter by role and location. Before applying, review the job description carefully for stack requirements like SQL, Python, Spark, or specific BI tools, since Qualcomm's analytics teams vary in their technical focus. Migrate Mate lists verified Data Analytics Engineer openings at Qualcomm filtered by sponsorship history, which helps you prioritize roles with an active track record over generic postings.
Which visa types does Qualcomm commonly use for Data Analytics Engineers?
Qualcomm sponsors a range of visa types for this function, including H-1B, H-1B1 visa for Chilean and Singaporean nationals, TN visa for Canadian and Mexican nationals, and F-1 OPT and CPT for students still in their academic program. For longer-term employment, Qualcomm also supports EB-2 and EB-3 Green Card petitions, which involve PERM labor certification filed with the Department of Labor before USCIS adjudicates the immigrant visa petition.
What qualifications does Qualcomm expect from Data Analytics Engineers?
Qualcomm's data analytics roles typically require a bachelor's or master's degree in computer science, statistics, data science, or a related engineering field. Hands-on experience with SQL, Python, and at least one cloud data platform is expected. Roles closer to the product or business intelligence side often add requirements around data visualization tools and cross-functional stakeholder communication, particularly within hardware or semiconductor product lines.
How do I manage my visa status during the hiring and onboarding timeline at Qualcomm?
If you're transitioning from F-1 OPT to H-1B, Qualcomm must file your H-1B petition in April for an October 1 start. If your OPT expires before October 1 and you have a STEM extension, you can bridge the gap with cap-gap protection under USCIS rules, which extends your work authorization automatically. Confirm your I-94 expiration date and OPT end date with Qualcomm's immigration team as early as possible to avoid authorization gaps during onboarding.