Data Engineering Manager Visa Sponsorship Jobs in California
California is one of the most active states for data engineering manager visa sponsorship, driven by major tech employers across the San Francisco Bay Area, Los Angeles, and San Diego. Companies like Google, Meta, Apple, and Salesforce regularly hire for this role. The state's concentration of data-intensive industries makes it a strong market for international candidates.
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Get Access To All JobsINTRODUCTION
The AIM Data Science team provides quantitative support, market understanding and a perspective to our partners throughout the organization, in close collaboration with the Ads and Commerce Finance team. Our success is measured by our ability to help partners make better, faster decisions. We prioritize insights over purely academic analyses. We focus on the most critical business issues, particularly engaged positioning and product features to drive the most significant impact. We aim to scale our impact by empowering partners with the tools they need to answer their own questions through clean datasets, automated dashboards, and clear documentation. We are responsible for translating data into clear business logic. We invest in data infrastructure, documentation, and metric definitions to ensure consistency and reliability.
As a Data Engineering Manager for Analytics, Insights and Measurement (AIM) and Enterprise Platform, you will help drive the goal of how large advertisers buy Google and third-party advertising inventory efficiently. You will be responsible for setting the team's direction, managing stakeholder relationships.
BASIC QUALIFICATIONS
- Bachelor's degree or equivalent practical experience.
- 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
- 5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal and external stacks.
- 3 years of experience in a leadership role (e.g., technical leadership or people management, supervision, or team leadership).
PREFERRED QUALIFICATIONS
- Advanced degree in a quantitative field such as: Statistics, Computer Science, Engineering, Mathematics, Economics, or Physics.
- 10 years of experience with statistical data analysis (data mining and data querying), modeling, experimentation, and managing analytical projects.
- 7 years of experience with statistical data analysis, modeling, experimentation, and causal inference to solve product and business problems.
- 5 years of experience in developing and managing metrics or evaluating programs/products.
- Experience in running experimentation-based decision-making processes, both quantitatively (inference, stats, etc.) and organizationally (discipline, alignment, stakeholder management).
- Excellent programming skills in SQL, Python or R.
Responsibilities
- Align executive cross-functional Ads stakeholders on a cross-functional process and discipline for the quantitative attribution of impact on key product initiatives.
- Provide thought leadership to executive leadership through proactive contributions; consistently using insights and analytics to drive decisions and alignment throughout the product organization.
- Define and report key performance indicators and launch impact as part of regular business reviews and contribute to metric-backed annual quarterly objectives and key results (OKR) setting.
- Build an understanding of the data sets used by Enterprise Platforms and partner teams, collaborating with Engineering teams to identify and address instrumentation gaps, ensuring accurate data collection for key functionalities, with a focus on our most impactful features.
- Anticipate and address issues as a trusted authority and critical domain expert. Conducting end-to-end problem-solving, including analysis and business cases.
COMPENSATION
The US base salary range for this full-time position is $186,000-$270,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
INTRODUCTION
The AIM Data Science team provides quantitative support, market understanding and a perspective to our partners throughout the organization, in close collaboration with the Ads and Commerce Finance team. Our success is measured by our ability to help partners make better, faster decisions. We prioritize insights over purely academic analyses. We focus on the most critical business issues, particularly engaged positioning and product features to drive the most significant impact. We aim to scale our impact by empowering partners with the tools they need to answer their own questions through clean datasets, automated dashboards, and clear documentation. We are responsible for translating data into clear business logic. We invest in data infrastructure, documentation, and metric definitions to ensure consistency and reliability.
As a Data Engineering Manager for Analytics, Insights and Measurement (AIM) and Enterprise Platform, you will help drive the goal of how large advertisers buy Google and third-party advertising inventory efficiently. You will be responsible for setting the team's direction, managing stakeholder relationships.
BASIC QUALIFICATIONS
- Bachelor's degree or equivalent practical experience.
- 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
- 5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal and external stacks.
- 3 years of experience in a leadership role (e.g., technical leadership or people management, supervision, or team leadership).
PREFERRED QUALIFICATIONS
- Advanced degree in a quantitative field such as: Statistics, Computer Science, Engineering, Mathematics, Economics, or Physics.
- 10 years of experience with statistical data analysis (data mining and data querying), modeling, experimentation, and managing analytical projects.
- 7 years of experience with statistical data analysis, modeling, experimentation, and causal inference to solve product and business problems.
- 5 years of experience in developing and managing metrics or evaluating programs/products.
- Experience in running experimentation-based decision-making processes, both quantitatively (inference, stats, etc.) and organizationally (discipline, alignment, stakeholder management).
- Excellent programming skills in SQL, Python or R.
Responsibilities
- Align executive cross-functional Ads stakeholders on a cross-functional process and discipline for the quantitative attribution of impact on key product initiatives.
- Provide thought leadership to executive leadership through proactive contributions; consistently using insights and analytics to drive decisions and alignment throughout the product organization.
- Define and report key performance indicators and launch impact as part of regular business reviews and contribute to metric-backed annual quarterly objectives and key results (OKR) setting.
- Build an understanding of the data sets used by Enterprise Platforms and partner teams, collaborating with Engineering teams to identify and address instrumentation gaps, ensuring accurate data collection for key functionalities, with a focus on our most impactful features.
- Anticipate and address issues as a trusted authority and critical domain expert. Conducting end-to-end problem-solving, including analysis and business cases.
COMPENSATION
The US base salary range for this full-time position is $186,000-$270,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Data Engineering Manager Job Roles in California
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Search Data Engineering Manager Jobs in CaliforniaData Engineering Manager Jobs in California: Frequently Asked Questions
Which companies sponsor visas for data engineering managers in California?
Large technology companies are the most consistent sponsors for data engineering manager roles in California. Google, Meta, Apple, Salesforce, Adobe, Uber, and Lyft have established sponsorship programs and regularly file H-1B petitions for senior engineering management positions. Enterprise software firms, financial technology companies headquartered in San Francisco, and large e-commerce platforms in the state also sponsor this role with regularity.
Which visa types are most common for data engineering manager roles in California?
The H-1B is the most common visa for data engineering managers in California, given the role typically requires a bachelor's degree or higher in computer science, engineering, or a related field. Candidates with extraordinary ability may qualify for the O-1A. Those transferring within a multinational company can explore the L-1A, which applies to managers and executives. Australian citizens may also qualify for the E-3 visa.
Which cities in California have the most data engineering manager sponsorship jobs?
The San Francisco Bay Area, including San Jose, Sunnyvale, Mountain View, and San Francisco itself, accounts for the largest share of data engineering manager sponsorship jobs in California. Los Angeles is a growing market, particularly in media technology, streaming, and fintech. San Diego has a smaller but active cluster tied to biotech and defense technology companies that manage significant data infrastructure.
How to find data engineering manager visa sponsorship jobs in California?
Migrate Mate is built specifically for international candidates seeking visa sponsorship roles in the U.S. You can filter directly for data engineering manager positions in California to see employers actively open to sponsorship. Because this is a senior-level role, it helps to look for companies with established H-1B filing histories in California, which Migrate Mate surfaces through its curated job listings.
Are there any California-specific considerations for data engineering manager sponsorship?
California's prevailing wage requirements under the H-1B program reflect the state's high cost of living, particularly in the Bay Area, meaning employers must meet Department of Labor wage levels that are among the highest in the country for this role. California's large university pipeline from UC Berkeley, UCLA, and Stanford also means competition for open roles is significant, though the volume of sponsoring employers in the state is correspondingly high.
What is the prevailing wage for sponsored data engineering manager jobs in California?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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