Data Science Engineer Jobs at Qualcomm with Visa Sponsorship
Data Science Engineer jobs at Qualcomm involve working across signal processing, device performance, and AI-driven media workflows. The company has a consistent track record of sponsoring work visas for this function, supporting candidates through both nonimmigrant and immigrant pathways from offer through Green Card.
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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 Science Engineer Jobs at Qualcomm
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Science Engineer Jobs at Qualcomm.
Get Access To All JobsTips for Finding Data Science Engineer Jobs at Qualcomm
Align Your Degree to Qualcomm's Stack
Qualcomm's Data Science Engineer roles frequently require a graduate degree in computer science, electrical engineering, or statistics. Confirm your transcripts reflect coursework in machine learning, signal processing, or applied mathematics before applying, since these fields map directly to their specialty occupation filings.
Target Roles With AI and DSP Overlap
Qualcomm's data science openings in media and entertainment often sit at the intersection of AI inference and digital signal processing. Filtering for roles that mention on-device AI, Snapdragon, or multimedia pipelines increases your chances of landing a team that actively sponsors international candidates.
Ask Recruiters About PERM Timeline Early
Qualcomm sponsors EB-2 and EB-3 Green Cards for qualifying engineers. During the offer stage, ask directly whether the role is earmarked for PERM sponsorship, since DOL's PERM process can take 12 to 18 months before an I-140 is filed.
Use Migrate Mate to Surface Verified Openings
Qualcomm posts Data Science Engineer roles across multiple channels, making it hard to identify which positions actively support visa sponsorship. Use Migrate Mate to browse verified openings filtered by visa type so you're only applying where H-1B or TN sponsorship is confirmed.
Prepare for H-1B Cap Timing if on OPT
If you're on F-1 OPT, Qualcomm can file your H-1B petition during the April cap season for an October 1 start. Confirm your OPT expiration date and STEM OPT eligibility with your DSO well before the March registration window opens with USCIS.
Clarify TN Eligibility for Canadian and Mexican Nationals
Canadian and Mexican nationals targeting Qualcomm data science roles may qualify for TN status under the computer systems analyst category, avoiding the H-1B lottery entirely. Verify the offered job title and duties align with DOL's TN classification before your offer letter is finalized.
Frequently Asked Questions
Does Qualcomm sponsor H-1B visas for Data Science Engineers?
Yes, Qualcomm sponsors H-1B visas for Data Science Engineers. The company participates in the annual H-1B cap lottery each spring and also supports cap-exempt filings in certain circumstances. If you're already on H-1B status with another employer, Qualcomm can file an H-1B transfer without waiting for a new cap season.
How do I apply for Data Science Engineer jobs at Qualcomm?
Applications go through Qualcomm's careers portal at qualcomm.com/careers. Search by role title and filter for positions in your target location. Tailoring your resume to highlight AI, machine learning, or signal processing experience is important since those skills align with how Qualcomm structures its data science teams. Migrate Mate also lists verified Qualcomm openings filtered by visa sponsorship type, which saves time if you're specifically seeking sponsored roles.
Which visa types does Qualcomm commonly use for Data Science Engineer roles?
Qualcomm sponsors H-1B and H-1B1 visas for most international Data Science Engineers, with H-1B being the primary path for candidates outside Chile and Singapore. F-1 OPT and STEM OPT extensions bridge the gap before H-1B approval. For permanent residency, Qualcomm files EB-2 and EB-3 petitions through the PERM labor certification process. TN visa status is available to Canadian and Mexican nationals in qualifying job categories.
What qualifications and experience does Qualcomm expect for Data Science Engineer roles?
Most Data Science Engineer roles at Qualcomm require a bachelor's or master's degree in computer science, electrical engineering, statistics, or a related quantitative field. Hands-on experience with machine learning frameworks, data pipeline development, and model deployment is expected. Roles tied to Qualcomm's media and entertainment work often also value familiarity with on-device AI inference, multimedia compression, or real-time processing systems.
How do I understand the visa sponsorship process timeline at Qualcomm?
Once you receive an offer, Qualcomm's immigration team typically engages an outside counsel to begin the Labor Condition Application with DOL, which must be certified before the H-1B petition is filed with USCIS. Standard processing runs three to five months. Premium processing through USCIS reduces adjudication to 15 business days but adds cost. If PERM is in scope, budget an additional 12 to 18 months for that stage before I-140 filing.