H-1B1 Singapore Visa Data Engineering Manager Jobs
Data Engineering Manager jobs with H-1B1 Singapore visa sponsorship are open to Singaporean nationals without a lottery draw. The annual cap of 5,400 sits well below demand, and your application goes directly to the U.S. consulate in Singapore, where approvals typically clear in days rather than months.
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Do you want to shape Amazon's experimentation and impact-measurement capabilities in the era of Generative AI? As we navigate the rapidly changing landscape of e-commerce, your role will be crucial in shaping how Amazon teams, sellers, and vendors optimize catalog listings for a superior customer experience. Join the Catalog Experimentation and Impact Measurement (CEM) team on our mission to create the best product listings that help customers make well-informed, fast buying decisions. We build the feedback loops that let Large Language Models and Amazon teams enrich product data through experimentation at Amazon scale.
What you'll own
In this role, you will lead the conceptualization, delivery, and worldwide adoption of the Catalog Experimentation Platform (CEP). Through experiments, we bring the voice of the customer to our business stakeholders. You will collaborate with economists to help users design experiments correctly, and guide them in interpreting outcomes generated through rigorous statistical analysis. You will advocate for decisions in the best interest of our customers even when the outcomes are unpleasant for the experimenters.
A central part of your charter is impact measurement. Measuring the impact of every initiative that intends to improve product data quality is crucial for prioritization decisions and for fine-tuning each initiative's strategy. CEM operates a two-part measurement approach: one that estimates how improvements in product data quality translate into incremental sales and customer benefit, and another through which partner teams run controlled experiments while the team reviews their design and aggregates results across the organization. You will collaborate with economists to identify and apply the best possible causal-inference methodology for each initiative, and you will extend the scope of the platform to make it the go-to destination at Amazon for measuring the impact of catalog improvement programs.
Finally, to make experimentation and impact measurement work at Amazon scale without compromising reliability, you will collaborate with your engineering counterparts to build systems for automation, self-service mechanisms, and guardrails.
Who you'll work with
You will partner closely with economists and scientists (for experiment design and causal inference), engineering counterparts (for automation, self-service, and guardrails), and the partner and enrichment teams across Amazon whose catalog programs depend on trustworthy impact measurement.
Key job responsibilities
- Work backwards from the customer experience to define strategy and build a product roadmap for the Catalog Experimentation Platform (CEP), used to run A/B experiments on catalog listings.
- Launch new products and features by partnering with CEP engineering and science teams.
- Drive adoption by partnering with the teams building large language models for the catalog and with business stakeholders across different product categories.
- Partner with economists and other product managers on the team to develop frameworks and shape how business stakeholders and leadership think about impact-measurement methodologies.
- Represent CEP in Amazon-wide forums on experimentation and impact measurement.
A day in the life
Learn about the strengths and challenges of experimentation platforms used across the industry. Develop product strategy — positioning, go-to-market, and competitive advantage — in collaboration with your engineering and science counterparts. Track key product metrics and communicate wins, misses, and learnings to your key stakeholders. Conduct office hours to guide experimentation users. Communicate strategy and key updates to org leadership through monthly flashes and business-review forums.
About the team
Amazon's customers rely on the completeness, consistency, and correctness of Amazon's product data to make well-informed purchase decisions, and improving the quality of that product data is a continuous process. Amazon Selection Catalog Systems (ASCS) is building the Catalog Experimentation and Impact Measurement platform (CEM), which enables teams across Amazon to make data-driven decisions about which product-data changes will simplify and improve the customer experience. It empowers its users to remove personal bias and let data guide decision-making by testing their hypotheses against a representative sample of a broader population. Not least, CEM helps large language models draw causal inferences between catalog-quality improvement actions and customer-experience metrics.
BASIC QUALIFICATIONS
- 5+ years of product or program management, product marketing, business development or technology experience
- Bachelor's degree
- Experience with feature delivery and tradeoffs of a product
- Experience owning/driving roadmap strategy and definition
- Experience with end to end product delivery
- Experience contributing to engineering discussions around technology decisions and strategy related to a product
- Experience managing technical products or online services
- Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning
PREFERRED QUALIFICATIONS
- Bachelor's degree in math/statistics/engineering or other equivalent quantitative discipline
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, WA, Seattle
COMPENSATION
- Salary Range: 151,200.00 - 204,600.00 USD annually
DESCRIPTION
Do you want to shape Amazon's experimentation and impact-measurement capabilities in the era of Generative AI? As we navigate the rapidly changing landscape of e-commerce, your role will be crucial in shaping how Amazon teams, sellers, and vendors optimize catalog listings for a superior customer experience. Join the Catalog Experimentation and Impact Measurement (CEM) team on our mission to create the best product listings that help customers make well-informed, fast buying decisions. We build the feedback loops that let Large Language Models and Amazon teams enrich product data through experimentation at Amazon scale.
What you'll own
In this role, you will lead the conceptualization, delivery, and worldwide adoption of the Catalog Experimentation Platform (CEP). Through experiments, we bring the voice of the customer to our business stakeholders. You will collaborate with economists to help users design experiments correctly, and guide them in interpreting outcomes generated through rigorous statistical analysis. You will advocate for decisions in the best interest of our customers even when the outcomes are unpleasant for the experimenters.
A central part of your charter is impact measurement. Measuring the impact of every initiative that intends to improve product data quality is crucial for prioritization decisions and for fine-tuning each initiative's strategy. CEM operates a two-part measurement approach: one that estimates how improvements in product data quality translate into incremental sales and customer benefit, and another through which partner teams run controlled experiments while the team reviews their design and aggregates results across the organization. You will collaborate with economists to identify and apply the best possible causal-inference methodology for each initiative, and you will extend the scope of the platform to make it the go-to destination at Amazon for measuring the impact of catalog improvement programs.
Finally, to make experimentation and impact measurement work at Amazon scale without compromising reliability, you will collaborate with your engineering counterparts to build systems for automation, self-service mechanisms, and guardrails.
Who you'll work with
You will partner closely with economists and scientists (for experiment design and causal inference), engineering counterparts (for automation, self-service, and guardrails), and the partner and enrichment teams across Amazon whose catalog programs depend on trustworthy impact measurement.
Key job responsibilities
- Work backwards from the customer experience to define strategy and build a product roadmap for the Catalog Experimentation Platform (CEP), used to run A/B experiments on catalog listings.
- Launch new products and features by partnering with CEP engineering and science teams.
- Drive adoption by partnering with the teams building large language models for the catalog and with business stakeholders across different product categories.
- Partner with economists and other product managers on the team to develop frameworks and shape how business stakeholders and leadership think about impact-measurement methodologies.
- Represent CEP in Amazon-wide forums on experimentation and impact measurement.
A day in the life
Learn about the strengths and challenges of experimentation platforms used across the industry. Develop product strategy — positioning, go-to-market, and competitive advantage — in collaboration with your engineering and science counterparts. Track key product metrics and communicate wins, misses, and learnings to your key stakeholders. Conduct office hours to guide experimentation users. Communicate strategy and key updates to org leadership through monthly flashes and business-review forums.
About the team
Amazon's customers rely on the completeness, consistency, and correctness of Amazon's product data to make well-informed purchase decisions, and improving the quality of that product data is a continuous process. Amazon Selection Catalog Systems (ASCS) is building the Catalog Experimentation and Impact Measurement platform (CEM), which enables teams across Amazon to make data-driven decisions about which product-data changes will simplify and improve the customer experience. It empowers its users to remove personal bias and let data guide decision-making by testing their hypotheses against a representative sample of a broader population. Not least, CEM helps large language models draw causal inferences between catalog-quality improvement actions and customer-experience metrics.
BASIC QUALIFICATIONS
- 5+ years of product or program management, product marketing, business development or technology experience
- Bachelor's degree
- Experience with feature delivery and tradeoffs of a product
- Experience owning/driving roadmap strategy and definition
- Experience with end to end product delivery
- Experience contributing to engineering discussions around technology decisions and strategy related to a product
- Experience managing technical products or online services
- Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning
PREFERRED QUALIFICATIONS
- Bachelor's degree in math/statistics/engineering or other equivalent quantitative discipline
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, WA, Seattle
COMPENSATION
- Salary Range: 151,200.00 - 204,600.00 USD annually
See all 83+ H-1B1 Singapore Visa Data Engineering Manager Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B1 Singapore Visa Data Engineering Manager Jobs.
Get Access To All JobsTips for Finding Visa Sponsorship as a Data Engineering Manager
Frame your credentials for U.S. specialty occupation standards
Your Singapore degree and data engineering certifications must map to a role requiring at least a bachelor's in a directly related field. Pull the O*NET profile for Computer and Information Systems Managers to confirm the field-of-study alignment before your employer files.
Target employers with active H-1B1 LCA filing history
Search Migrate Mate to filter Data Engineering Manager roles by verified H-1B1 visa sponsorship history. Employers who've filed Labor Condition Applications for this occupation already understand the process and won't hesitate at the consulate step.
Negotiate who absorbs the LCA prevailing-wage requirement
Your offer must meet DOL prevailing wage for your location and job zone. Use the OFLC Wage Search to look up the Level III or IV wage for your target metro before entering salary negotiations, so you know the floor your employer must clear.
Clarify your employer's E-Verify enrollment before accepting an offer
H-1B1 visa employers aren't automatically required to use E-Verify unless they're federal contractors or operate in a mandatory state. Confirming enrollment early prevents I-9 complications when you start, especially if you're transitioning from an existing U.S. visa status.
Time your consulate appointment around your current status expiry
H-1B1 visa is processed at the U.S. Embassy in Singapore, not through USCIS. If you're already in the U.S. on another visa, plan your travel window carefully, as you'll need to attend the interview in person and your current status must remain valid through departure.
Prepare for annual renewal cycles specific to H-1B1
Unlike H-1B visa, H-1B1 visa is approved in one-year increments with no multi-year extension option. Your employer's HR team needs to initiate the LCA renewal process at least 90 days before your status expires to avoid a gap in your work authorization.
Frequently Asked Questions
Does a Data Engineering Manager role qualify as a specialty occupation for H-1B1 purposes?
Yes, Data Engineering Manager roles typically qualify. USCIS requires the position to demand a bachelor's degree or higher in a directly related field such as computer science, data engineering, or information systems. Because the role combines technical data architecture decisions with team leadership, the specialized degree requirement is straightforward to document, making it a cleaner petition than generalist management titles.
How does the H-1B1 Singapore visa compare to H-1B for Data Engineering Manager jobs?
The H-1B1 visa skips the lottery entirely, so a Singaporean national with a qualifying job offer can apply directly at the consulate rather than waiting for a random selection result. The trade-off is that H-1B1 is approved in one-year increments rather than three, so your employer's HR team needs to plan annual renewals. For a Data Engineering Manager role, the specialty occupation threshold is the same under both visas.
How do I find Data Engineering Manager jobs where the employer already understands H-1B1 Singapore sponsorship?
Use Migrate Mate to search for Data Engineering Manager roles filtered by verified H-1B1 visa sponsorship history. Employers who've previously filed Labor Condition Applications for this visa type already have HR and legal processes in place, which shortens the offer-to-approval timeline significantly and reduces the chance of the employer backing out during the consulate filing stage.
What prevailing wage level applies to Data Engineering Manager positions under H-1B1?
Data Engineering Manager roles typically fall at DOL wage Level III or Level IV, depending on supervisory scope and years of experience. Use the OFLC Wage Search and input the relevant occupation code for your target city before negotiating your offer. Your employer's LCA must certify a salary at or above the prevailing wage for your specific location, and the consulate will verify this during adjudication.
Can I change employers while on H-1B1 status if I'm already working as a Data Engineering Manager in the U.S.?
H-1B1 visa doesn't have the portability provisions that H-1B carries under AC21, so you can't start work with a new employer the moment they file. Your new employer must have a certified LCA and you'll generally need to attend a consulate interview in Singapore before beginning the new role. Planning your transition timeline around this requirement is essential to avoid an unauthorized work gap.