J-1 Visa Analytics Engineer Jobs
Analytics Engineer roles in the United States are accessible to international professionals through the J-1 visa under the Trainee or Research Scholar category, depending on your career stage. Designated sponsors issue the DS-2019 and coordinate sponsorship with your host employer, covering data pipeline, modeling, and analytics platform work.
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Get Access To All JobsBusiness Intelligence (BI) Analytics Intern
Location: San Mateo, CA (Hybrid)
Duration: Summer 2026 (12 weeks)
Compensation: $5K/mo
Reports to: Head of RevOps
Company: Bedrock Data
About Bedrock
Data is moving faster than security can keep up, fragmented across clouds, SaaS apps, and AI systems, without the context teams need to protect it. Bedrock Data built the industry's first Metadata Lake to solve this: a living map of all your data that shows what it is, where it lives, who's using it, and how sensitive it is, without ever moving the data itself. This lets enterprises automate security and governance at scale, making data protection continuous and invisible instead of manual and disruptive. Global leaders in technology, finance, healthcare, and biotech trust Bedrock Data to make data security operational. With a $25M Series A led by Greylock, Bedrock is led by repeat founders and technologists who built industry-leading enterprise platforms at Sumo Logic, Rubrik, and Cohesity. Learn more at bedrockdata.ai.
The Role
As our BI Analytics Intern, you won't just be pulling data, you will be building the systems that allow our team to understand it. You will play a foundational role in standing up our analytics environment in Salesforce, extracting actionable insights from transcripts, and establishing a source of truth for our internal data assets to ensure our Sales and Finance teams are completely aligned.
Key Responsibilities
Sales & Forecasting Dashboards: Take the lead on designing and deploying custom analytics within Salesforce. You will establish KPI reporting for pipeline health and sales velocity, and build robust forecasting dashboards to give leadership clear visibility into projected revenue and quota attainment. Audit existing Salesforce data quality and work with stakeholders to clean, normalize, and structure data for reliable reporting
Finance & RevOps Reporting: Bridge the gap between sales activity and financial performance. You will design finance dashboards in Salesforce to track critical metrics (e.g., ARR, pipeline, and win rates), ensuring the Finance team has real-time access to accurate, reliable data. You will help establish a cadence of automated, self-serve reporting for the Sales and Finance leadership teams
Transcript & LLM Data Integration: You will analyze LLM-generated transcripts, summaries, and sales call data to uncover trends in buyer sentiment, objection handling, and win/loss drivers.
Build the Internal Data Repository: Establish and structure an internal knowledge repository. You will document data models and build a data dictionary to ensure our analytics practices are scalable and easily accessible to the rest of the company.
Cross-Functional Collaboration: Partner directly with Sales, Finance, RevOps, and Product teams to understand their unique data needs and translate business questions into technical requirements.
What We’re Looking For
Education: Currently pursuing (or recently graduated with) a degree in Business Analytics, Finance, Data Science, Information Systems, Economics, or a related field.
Business Acumen: A solid understanding of basic sales and financial metrics (pipeline coverage, forecasting, ARR).
AI Curiosity: A strong interest in Large Language Models (LLMs) and how conversational AI is transforming business intelligence.
Organizational Skills: A systems-thinker who enjoys building structured documentation and keeping complex information organized.
Bonus Points
Familiarity with Python or R for data manipulation.
Familiarity in SQL and experience with data visualization tools.
Prior exposure to Salesforce (or similar CRM platforms); you understand how sales and revenue data is structured (Leads, Opportunities, Accounts).
Curiosity building foundational analytics.
What You’ll Get Out of It
High-Impact Projects: You will build revenue and data infrastructure that the company will rely on long after your internship ends.
Mentorship: Work closely with senior leaders across multiple departments (Sales, Finance, Ops) who are invested in your growth.
Hands-on AI Experience: Real-world experience analyzing unstructured data using cutting-edge LLM tooling.
Business Intelligence (BI) Analytics Intern
Location: San Mateo, CA (Hybrid)
Duration: Summer 2026 (12 weeks)
Compensation: $5K/mo
Reports to: Head of RevOps
Company: Bedrock Data
About Bedrock
Data is moving faster than security can keep up, fragmented across clouds, SaaS apps, and AI systems, without the context teams need to protect it. Bedrock Data built the industry's first Metadata Lake to solve this: a living map of all your data that shows what it is, where it lives, who's using it, and how sensitive it is, without ever moving the data itself. This lets enterprises automate security and governance at scale, making data protection continuous and invisible instead of manual and disruptive. Global leaders in technology, finance, healthcare, and biotech trust Bedrock Data to make data security operational. With a $25M Series A led by Greylock, Bedrock is led by repeat founders and technologists who built industry-leading enterprise platforms at Sumo Logic, Rubrik, and Cohesity. Learn more at bedrockdata.ai.
The Role
As our BI Analytics Intern, you won't just be pulling data, you will be building the systems that allow our team to understand it. You will play a foundational role in standing up our analytics environment in Salesforce, extracting actionable insights from transcripts, and establishing a source of truth for our internal data assets to ensure our Sales and Finance teams are completely aligned.
Key Responsibilities
Sales & Forecasting Dashboards: Take the lead on designing and deploying custom analytics within Salesforce. You will establish KPI reporting for pipeline health and sales velocity, and build robust forecasting dashboards to give leadership clear visibility into projected revenue and quota attainment. Audit existing Salesforce data quality and work with stakeholders to clean, normalize, and structure data for reliable reporting
Finance & RevOps Reporting: Bridge the gap between sales activity and financial performance. You will design finance dashboards in Salesforce to track critical metrics (e.g., ARR, pipeline, and win rates), ensuring the Finance team has real-time access to accurate, reliable data. You will help establish a cadence of automated, self-serve reporting for the Sales and Finance leadership teams
Transcript & LLM Data Integration: You will analyze LLM-generated transcripts, summaries, and sales call data to uncover trends in buyer sentiment, objection handling, and win/loss drivers.
Build the Internal Data Repository: Establish and structure an internal knowledge repository. You will document data models and build a data dictionary to ensure our analytics practices are scalable and easily accessible to the rest of the company.
Cross-Functional Collaboration: Partner directly with Sales, Finance, RevOps, and Product teams to understand their unique data needs and translate business questions into technical requirements.
What We’re Looking For
Education: Currently pursuing (or recently graduated with) a degree in Business Analytics, Finance, Data Science, Information Systems, Economics, or a related field.
Business Acumen: A solid understanding of basic sales and financial metrics (pipeline coverage, forecasting, ARR).
AI Curiosity: A strong interest in Large Language Models (LLMs) and how conversational AI is transforming business intelligence.
Organizational Skills: A systems-thinker who enjoys building structured documentation and keeping complex information organized.
Bonus Points
Familiarity with Python or R for data manipulation.
Familiarity in SQL and experience with data visualization tools.
Prior exposure to Salesforce (or similar CRM platforms); you understand how sales and revenue data is structured (Leads, Opportunities, Accounts).
Curiosity building foundational analytics.
What You’ll Get Out of It
High-Impact Projects: You will build revenue and data infrastructure that the company will rely on long after your internship ends.
Mentorship: Work closely with senior leaders across multiple departments (Sales, Finance, Ops) who are invested in your growth.
Hands-on AI Experience: Real-world experience analyzing unstructured data using cutting-edge LLM tooling.
See all J-1 Visa Analytics Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new J-1 Visa Analytics Engineer Jobs.
Get Access To All JobsTips for Finding J-1 Visa Sponsorship as an Analytics Engineer
Align your training plan with analytics deliverables
Your DS-2019 training plan must map your day-to-day work to concrete learning objectives. Document specific tools you'll use, such as dbt, Spark, or Snowflake, and the competencies each phase builds. Vague plans get rejected by designated sponsors.
Verify your J-1 category before applying
If you're currently enrolled and completing a practicum, the Intern category applies. If you've graduated and have relevant professional experience, you qualify under Trainee. Applying under the wrong category delays your DS-2019 issuance and can void a job offer.
Search for employers using Migrate Mate
Use Migrate Mate to filter Analytics Engineer roles at U.S. companies that have hosted J-1 visa exchange visitors before. Targeting employers familiar with the host-organization model saves you weeks of educating hiring managers about how J-1 sponsorship works.
Confirm the host employer will sign the training agreement
The hiring company must formally agree to serve as a host organization and co-sign the training plan your designated sponsor prepares. Get written confirmation from the employer's HR team before accepting any offer, since some companies decline after initial interest.
Check whether your role triggers the two-year home residency requirement
Analytics Engineers funded by a government or international organization, or whose home country has a skills shortage in data and technology fields, may face a two-year home residency requirement after their program ends. Review your J-1 visa stamp and DS-2019 for the section 212(e) notation before planning next steps.
Request a wage review against OFLC Wage Search benchmarks
Ask your prospective host employer to verify your offered compensation against prevailing wage levels using the OFLC Wage Search before your training plan is submitted. A wage that falls below the applicable level can trigger sponsor rejection or DOL scrutiny during program monitoring.
Analytics Engineer J-1 Visa: Frequently Asked Questions
Which J-1 program category covers Analytics Engineer roles?
Most Analytics Engineer positions fall under the Trainee category if you hold a relevant degree and have at least one year of professional experience outside the United States. If you're completing a degree program and the role is part of a practicum or curriculum requirement, the Intern category applies instead. Research Scholar is reserved for postdoctoral or faculty-level analytics research at universities or research institutes, not industry analytics roles.
Who actually sponsors my J-1 visa for an Analytics Engineer position?
Your J-1 sponsor is a U.S. Department of State-designated organization, such as Cultural Vistas, AIPT, or IIE, not your hiring employer. The employer functions as the host organization. The designated sponsor issues your DS-2019, monitors program compliance, and maintains the legal relationship with the State Department. Your host employer signs the training plan but is not the visa sponsor in any legal sense.
How do I find U.S. employers open to hosting J-1 Analytics Engineers?
Use Migrate Mate to identify Analytics Engineer openings at companies that have prior experience working with J-1 exchange visitors. Many employers are unfamiliar with the host-organization model and the training plan requirement, so targeting companies with existing J-1 experience significantly reduces friction during hiring. Focusing on data-intensive industries like fintech, health tech, and enterprise SaaS also helps, since these employers commonly engage international talent pipelines.
Can I switch employers mid-program if a better Analytics Engineer role comes up?
Changing host employers during a J-1 program requires your designated sponsor's approval and typically necessitates an amended or new DS-2019. The new host must agree to co-sign a revised training plan and meet the sponsor's host-organization requirements. Switching is possible but not guaranteed, and you cannot begin work at the new employer until the sponsor formally approves the change. Plan timeline accordingly, as the process can take several weeks.
What should my J-1 training plan include for an Analytics Engineer role?
A strong training plan for this role specifies the technical stack you'll work with, including data modeling tools, warehouse platforms, and orchestration frameworks, and ties each phase to measurable skills you're developing. It should outline rotation periods if applicable, describe how the experience differs from what's available in your home country, and include supervision details. Designated sponsors will reject plans that read as standard job descriptions rather than structured learning programs.