Analytics Engineer Jobs in USA with Visa Sponsorship
Analytics engineers have solid visa sponsorship prospects since the role sits at the intersection of data engineering and analytics, which employers can easily justify as a specialty occupation. H-1B visa is the standard path, and you'll find sponsorship at tech companies, large enterprises with data teams, and consulting firms. TN visas work for Canadians and Mexicans under the engineer or computer systems analyst category. Having experience with tools like dbt, SQL, and Python strengthens both your job prospects and your visa case. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsINTRODUCTION
Secure Every Identity, from AI to Human
Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.
This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.
ABOUT THE JOB
The Global Data & Insights Team
Okta's Enterprise Data & Insights team powers the data infrastructure that drives decision-making across the company by building reliable pipelines, scalable data platforms, and production-grade data products. We partner closely with internal Data and Insights Analysts as well as external Okta Product teams to unlock business value through robust data architecture, efficient data movement, and the engineering foundations that make data trustworthy at scale.
ROLE AND RESPONSIBILITIES
The Senior Analytics Engineer, Enterprise Opportunity
We are seeking a Senior Analytics Engineer to support the Enterprise by building reliable, well-modeled, and trusted data for reporting, decision-making, and emerging AI use cases.
This role sits at the intersection of business context and technical execution. You will design scalable data models, define consistent business logic, and help establish a strong semantic foundation that enables both human analytics and machine-driven intelligence.
You will partner closely with Finance, People and Company Operations stakeholders, Data Analysts, and Data Engineers to ensure data is accurate, consistent, and easy to consume; whether through dashboards, self-service exploration, or AI-powered workflows.
What you’ll be doing
Data Modeling & Semantics
- Design, build, and maintain scalable data models using dbt and Snowflake
- Define and standardize core Finance, HR and Enterprise level metrics (e.g., revenue, ARR, billing, Attrition, Executive Insights, Security) with clear, governed logic
- Establish consistent modeling patterns, naming conventions, and semantic clarity across datasets
- Contribute to a shared semantic layer that supports both analytics and AI use cases
AI-Ready Data & Snowflake Ecosystem
- Prepare high-quality, well-governed datasets for use with Snowflake Cortex and Snowflake Intelligence
- Enable structured data foundations that support LLM-powered use cases, semantic querying, and intelligent applications
- Ensure data is context-rich, well-documented, and aligned with business meaning to improve AI accuracy and trust
Data Quality, Governance & Trust
- Implement robust testing, validation, and documentation practices in dbt
- Ensure consistency across reports and dashboards through shared definitions and reusable models
- Apply data governance best practices, including access controls, lineage, and auditability
- Partner across teams to establish clear ownership and accountability for data assets
Collaboration & Delivery
- Partner with Finance, Analysts, and cross-functional stakeholders to translate business needs into data solutions
- Support self-service analytics by building intuitive, reusable datasets
- Contribute to scalable data workflows that balance immediate business needs with long-term maintainability
- Work within an agile environment, contributing to planning, prioritization, and continuous improvement
AI and Data Mindset
- Demonstrate an AI-first mindset, thinking beyond data models and dashboards to how data can power intelligent systems and decision-making
- Understand the importance of well-modeled, well-documented, and semantically clear data for AI and LLM-based use cases
- A level of comfort leveraging AI-assisted workflows to improve productivity, code quality, and consistency
- Curiosity for emerging capabilities in platforms like Snowflake Cortex and Snowflake Intelligence, and how they can be applied to Enterprise analytics
BASIC QUALIFICATIONS
- 5–8+ years of experience in Analytics Engineering, Data Engineering, or similar roles
- Strong SQL skills and experience building analytics-ready data models
- Mentorship & Engineering Excellence: Mentorship, raising the technical bar, establishing organization-wide standards for dbt/SQL quality and CI/CD
- Hands-on experience with dbt and Snowflake or other ETL, Modeling and database platforms
- Solid understanding of data modeling principles, including dimensional modeling and semantic design
- Ability to navigate highly ambiguous business challenges, translating vague, complex, or competing goals from executive stakeholders into clear, actionable, and robust data solutions
- Experience translating business requirements into clear, maintainable data logic
- Familiarity with SaaS metrics and Finance and People data (e.g., ARR, revenue recognition, billing, attrition etc.)
- Experience with data quality, testing, and documentation best practices
- Exposure to Python, R, or data processing frameworks (e.g., PySpark) is a plus
- Experience with BI tools such as Tableau or Looker
- Strong communication skills and ability to work across technical and business teams
PREFERRED QUALIFICATIONS
What you can look forward to as an Okta employee!
- Amazing Benefits
- Making Social Impact
- Fostering Diversity, Equity, Inclusion and Belonging at Okta
- Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today!
COMPENSATION
The annual base salary range for this position for candidates located in the San Francisco Bay area is between:
$132,000 — $182,000 USD
The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington is between:
$118,000 — $162,000 USD
Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies.
Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.
Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/.
LI-HM2
LI-Hybrid
P24715_3413656
INTRODUCTION
Secure Every Identity, from AI to Human
Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.
This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.
ABOUT THE JOB
The Global Data & Insights Team
Okta's Enterprise Data & Insights team powers the data infrastructure that drives decision-making across the company by building reliable pipelines, scalable data platforms, and production-grade data products. We partner closely with internal Data and Insights Analysts as well as external Okta Product teams to unlock business value through robust data architecture, efficient data movement, and the engineering foundations that make data trustworthy at scale.
ROLE AND RESPONSIBILITIES
The Senior Analytics Engineer, Enterprise Opportunity
We are seeking a Senior Analytics Engineer to support the Enterprise by building reliable, well-modeled, and trusted data for reporting, decision-making, and emerging AI use cases.
This role sits at the intersection of business context and technical execution. You will design scalable data models, define consistent business logic, and help establish a strong semantic foundation that enables both human analytics and machine-driven intelligence.
You will partner closely with Finance, People and Company Operations stakeholders, Data Analysts, and Data Engineers to ensure data is accurate, consistent, and easy to consume; whether through dashboards, self-service exploration, or AI-powered workflows.
What you’ll be doing
Data Modeling & Semantics
- Design, build, and maintain scalable data models using dbt and Snowflake
- Define and standardize core Finance, HR and Enterprise level metrics (e.g., revenue, ARR, billing, Attrition, Executive Insights, Security) with clear, governed logic
- Establish consistent modeling patterns, naming conventions, and semantic clarity across datasets
- Contribute to a shared semantic layer that supports both analytics and AI use cases
AI-Ready Data & Snowflake Ecosystem
- Prepare high-quality, well-governed datasets for use with Snowflake Cortex and Snowflake Intelligence
- Enable structured data foundations that support LLM-powered use cases, semantic querying, and intelligent applications
- Ensure data is context-rich, well-documented, and aligned with business meaning to improve AI accuracy and trust
Data Quality, Governance & Trust
- Implement robust testing, validation, and documentation practices in dbt
- Ensure consistency across reports and dashboards through shared definitions and reusable models
- Apply data governance best practices, including access controls, lineage, and auditability
- Partner across teams to establish clear ownership and accountability for data assets
Collaboration & Delivery
- Partner with Finance, Analysts, and cross-functional stakeholders to translate business needs into data solutions
- Support self-service analytics by building intuitive, reusable datasets
- Contribute to scalable data workflows that balance immediate business needs with long-term maintainability
- Work within an agile environment, contributing to planning, prioritization, and continuous improvement
AI and Data Mindset
- Demonstrate an AI-first mindset, thinking beyond data models and dashboards to how data can power intelligent systems and decision-making
- Understand the importance of well-modeled, well-documented, and semantically clear data for AI and LLM-based use cases
- A level of comfort leveraging AI-assisted workflows to improve productivity, code quality, and consistency
- Curiosity for emerging capabilities in platforms like Snowflake Cortex and Snowflake Intelligence, and how they can be applied to Enterprise analytics
BASIC QUALIFICATIONS
- 5–8+ years of experience in Analytics Engineering, Data Engineering, or similar roles
- Strong SQL skills and experience building analytics-ready data models
- Mentorship & Engineering Excellence: Mentorship, raising the technical bar, establishing organization-wide standards for dbt/SQL quality and CI/CD
- Hands-on experience with dbt and Snowflake or other ETL, Modeling and database platforms
- Solid understanding of data modeling principles, including dimensional modeling and semantic design
- Ability to navigate highly ambiguous business challenges, translating vague, complex, or competing goals from executive stakeholders into clear, actionable, and robust data solutions
- Experience translating business requirements into clear, maintainable data logic
- Familiarity with SaaS metrics and Finance and People data (e.g., ARR, revenue recognition, billing, attrition etc.)
- Experience with data quality, testing, and documentation best practices
- Exposure to Python, R, or data processing frameworks (e.g., PySpark) is a plus
- Experience with BI tools such as Tableau or Looker
- Strong communication skills and ability to work across technical and business teams
PREFERRED QUALIFICATIONS
What you can look forward to as an Okta employee!
- Amazing Benefits
- Making Social Impact
- Fostering Diversity, Equity, Inclusion and Belonging at Okta
- Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today!
COMPENSATION
The annual base salary range for this position for candidates located in the San Francisco Bay area is between:
$132,000 — $182,000 USD
The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington is between:
$118,000 — $162,000 USD
Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies.
Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.
Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/.
LI-HM2
LI-Hybrid
P24715_3413656
See all 13,946+ Analytics Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Analytics Engineer roles.
Get Access To All JobsTips for Finding Visa Sponsorship as an Analytics Engineer
Become proficient in dbt and the modern data stack
dbt is the core tool that defines the analytics engineer role. Learn dbt Cloud or dbt Core, including testing, documentation, and package management. Pairing dbt skills with Snowflake or BigQuery experience positions you for roles at companies that have adopted the modern data stack.
Target companies that have established analytics engineering teams
Companies like Spotify, GitLab, dbt Labs, HashiCorp, and JetBlue have publicly invested in analytics engineering functions. Tech companies, fintech firms, and data-mature startups are the most likely employers for this role and tend to have sponsorship-friendly hiring practices.
Master dimensional data modeling
Kimball dimensional modeling and activity schema design are foundational to the analytics engineer role. Employers expect you to design star and snowflake schemas that balance query performance with maintainability. Strong modeling skills are a key differentiator in technical interviews for this position.
Contribute to the dbt open-source community
The dbt community is unusually active and visible through dbt Community Slack, open-source packages, and blog posts. Publishing dbt packages, writing about data modeling patterns, or contributing to dbt documentation builds your professional reputation and can connect you with hiring managers at sponsoring companies.
Learn data quality and testing frameworks
Analytics engineers are responsible for data reliability. Experience with dbt tests, Great Expectations, or elementary-data makes you more attractive to employers who need someone to build trusted data pipelines. This testing expertise is harder to find domestically, which can strengthen the employer's case for sponsorship.
Analytics Engineer jobs are hiring across the US. Find yours.
Find Analytics Engineer JobsFrequently Asked Questions
What is an analytics engineer and do these roles get visa sponsorship?
Analytics engineers bridge the gap between data engineering and analytics by building the data models and transformation pipelines that analysts and data scientists rely on. This is a rapidly growing role at tech companies and data-driven organizations. Because it requires specialized skills in SQL, dbt, and data modeling, analytics engineer positions can qualify for H-1B sponsorship under computer occupation SOC codes.
What tools should I know for analytics engineer roles?
dbt (data build tool) is the defining tool of this role. Beyond dbt, you should be proficient in SQL, familiar with cloud data warehouses like Snowflake, BigQuery, or Databricks, and comfortable with version control using Git. Knowledge of data modeling techniques like Kimball dimensional modeling and data quality testing frameworks rounds out the expected skill set.
How does the analytics engineer role differ from data engineer for visa classification?
Both roles can qualify for H-1B under similar SOC codes, but their focus areas differ. Data engineers build infrastructure and pipelines to move and store data, while analytics engineers transform and model data specifically for analytical consumption. Analytics engineers work more closely with business stakeholders and typically require stronger SQL and business logic skills than traditional data engineers.
Can analytics engineers qualify for STEM OPT?
Yes, analytics engineer roles can qualify for STEM OPT if your degree is in a STEM-designated field such as computer science, data science, or information systems. The 24-month STEM extension provides up to 36 months of total work authorization, which is particularly valuable given that many companies prefer to evaluate analytics engineers on their data modeling work before initiating H-1B sponsorship.
What is the prevailing wage requirement for sponsored Analytics Engineer jobs?
When a U.S. employer sponsors a foreign worker for a work visa, they are legally required to pay at least the "prevailing wage" — the average wage paid to workers in the same occupation, in the same geographic area, with similar experience. This is set by the Department of Labor to prevent employers from hiring foreign workers at below-market rates. The prevailing wage varies significantly by role, location, and experience level — for example, a analytics engineer in California will have a different prevailing wage than the same role in a smaller state. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search.
How to find Analytics Engineer jobs with visa sponsorship?
To find Analytics Engineer jobs with visa sponsorship, use Migrate Mate, which specializes in connecting international talent with sponsoring employers. Focus on tech companies, fintech firms, and data-driven startups that commonly sponsor H-1B, O-1, and other work visas for analytics roles. These employers actively seek skilled professionals to build data pipelines, create dashboards, and optimize business intelligence systems.
See which Analytics Engineer employers are hiring and sponsoring visas right now.
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