H-1B Visa Insights Analyst Jobs
Insights Analyst roles qualify for H-1B sponsorship when the position requires a bachelor's degree or higher in a directly related field such as statistics, data science, economics, or business analytics. Employers in tech, finance, healthcare, and market research regularly file H-1B petitions for this occupation, making it a viable path for international professionals with analytical credentials.
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Get Access To All JobsMeet the Moment with Alteryx
We're living through a once-in-a-generation shift in how work gets done. Data, automation, and AI are quickly becoming the center of every business decision - and Alteryx is leading the transformation.
You'll be working on the challenges that sit at the heart of modern business. No matter your role, the work you do will help organizations move faster, see more clearly, and tackle questions that used to feel impossible.
If you're ready to meet the moment with innovation, curiosity, and excellence, there's a place for you here.
Alteryx is searching for an Engineering Intelligence Analyst (Engineering Insights Team). This position is remote-friendly.
Position Overview:
We are building a data-driven understanding of how our engineering organization operates, and we’re looking for a Data Analyst focused on Engineering Intelligence to help us do it.
This role sits at the intersection of engineering, data, and operational excellence. Your mission is to transform engineering signals into insights that help us improve software quality, productivity, reliability, and cost efficiency.
You will analyze data from across the software development lifecycle (SDLC), from pull requests and CI/CD pipelines to service reliability metrics and incident management, and translate it into dashboards and insights that guide engineering leaders.
If you are passionate about understanding how engineering organizations work and how they can improve, this role is for you.
What You’ll Work On:
Engineering Effectiveness & SDLC Metrics
You will help measure and improve how our engineering organization builds and operates software. Examples of metrics you will analyze include:
- Development & productivity
- Pull request volume and cycle time
- Code review latency
- Deployment frequency
- Lead time for changes
- Change failure rate
- Reliability & operations
- SLO / SLA performance
- Incident and escalation patterns
- Engineering quality
- Defect trends
- Incident root causes
- Platform adoption
- Usage of internal platforms and services
- Adoption of engineering standards and best practices
- Engineering cost efficiency
- Infrastructure cost trends
- Cost per service / team
- Efficiency of engineering investments
Build Data Products for Engineering
You will create data products used daily by engineering leaders, including:
- Engineering health dashboards
- Service reliability dashboards
- Operational insights for engineering managers
- Executive views of engineering performance
- Adoption dashboards for internal platforms
Dashboards will primarily be built using Superset.
Data Pipelines & Analysis
You will work directly with engineering data systems. Responsibilities include:
- Writing advanced SQL queries to analyze engineering data
- Building lightweight Python pipelines to aggregate and process signals
- Integrating data from sources such as:
- Git repositories (PRs, commits)
- CI/CD systems
- Incident management systems
- Observability platforms
- Ticketing systems
- Cost management tools
You will help ensure that engineering metrics are accurate, consistent, and trusted across the organization.
Generate Insights That Drive Decisions
Beyond dashboards, your work will focus on finding meaningful patterns in engineering data. Examples include:
- Identifying bottlenecks in the development process
- Detecting reliability risks early
- Understanding operational load across teams
- Measuring whether internal platform investments are working
- Connecting engineering activity with infrastructure costs
You will translate complex datasets into clear insights and recommendations for engineering leadership.
Collaborate Across Engineering
This role requires deep collaboration with engineering teams. You will work closely with:
- Engineering managers
- Platform and infrastructure teams
- DevOps / SRE
- FinOps
- Engineering leadership
You will help define consistent engineering KPIs and ensure teams are producing the right operational data.
Qualifications
Technical Skills
- Strong SQL skills
- Experience using Python for data analysis or pipelines
- Experience building dashboards in Superset, Tableau, Looker, or similar BI tools
- Experience working with complex operational datasets
- Familiarity with data modeling and metric definitions
Engineering Awareness
You should be comfortable working with engineering concepts such as:
- Pull Requests (PRs)
- CI/CD pipelines
- Software Development Lifecycle (SDLC)
- Service Level Objectives (SLOs)
- Incident management
- Escalation tickets
- Service reliability metrics
You don’t need to be a software engineer, but you should enjoy working closely with engineers and understanding how systems are built and operated.
Analytical & Communication Skills
- Strong analytical thinking
- Ability to translate ambiguous questions into measurable metrics
- Ability to communicate insights clearly to technical and leadership audiences
- Strong attention to data quality and metric consistency
What Success Looks Like:
Within your first months:
- Engineering leaders have clear dashboards showing service health and engineering productivity
- Reliable metrics exist for SDLC performance and operational health
- Engineering leadership can easily track reliability, quality, and adoption of platforms
Over time:
- Engineering decisions become data-driven
- Operational risks are surfaced early through metrics
- Platform investments can be evaluated through measurable adoption
- The organization develops a shared understanding of engineering effectiveness
Why This Role Is Exciting:
Engineering organizations generate enormous amounts of operational data — but very few companies truly understand it. This role will help us answer questions like:
- Are we becoming more productive or slower over time?
- Are our systems getting more reliable?
- Are our platform investments paying off?
- Where are engineers spending their time?
- Are we scaling engineering efficiently and sustainably?
You will help build the operating intelligence layer for engineering.
Compensation:
Alteryx is committed to fair, equitable, and transparent compensation. Final compensation is determined by several factors, including but not limited to relevant work experience, education, certifications, skills, and geographic location.
The salary range for this role in the United States is $118,700 - $153,900.
Bonus payouts are based on individual and company performance.
In addition to base pay and bonus eligibility, this role includes clear forms of additional compensation, such as:
- A monthly Connectivity Plus stipend of $150 to support remote work-related expenses
- An annual $200 home office reimbursement
Alteryx offers a comprehensive benefits package designed to support your health, financial security, and overall well-being, including:
- Medical, dental, and vision coverage
- 401(k) with company match
- Paid parental leave, caregiver leave, and flexible time off
- Mental health support and wellness reimbursement
- Career development and education assistance
Interested? Learn more and apply today at alteryx.com/careers!
LI-EM1
LI-REMOTE
Find yourself checking a lot of these boxes but doubting whether you should apply? At Alteryx, we support a growth mindset for our associates through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences.
Benefits & Perks:
Alteryx has amazing benefits for all Associates which can be viewed here.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Alteryx will consider for employment qualified applicants with arrest and conviction records.
This position involves access to software/technology that is subject to U.S. export controls. Any job offer made will be contingent upon the applicant’s capacity to serve in compliance with U.S. export controls.
Meet the Moment with Alteryx
We're living through a once-in-a-generation shift in how work gets done. Data, automation, and AI are quickly becoming the center of every business decision - and Alteryx is leading the transformation.
You'll be working on the challenges that sit at the heart of modern business. No matter your role, the work you do will help organizations move faster, see more clearly, and tackle questions that used to feel impossible.
If you're ready to meet the moment with innovation, curiosity, and excellence, there's a place for you here.
Alteryx is searching for an Engineering Intelligence Analyst (Engineering Insights Team). This position is remote-friendly.
Position Overview:
We are building a data-driven understanding of how our engineering organization operates, and we’re looking for a Data Analyst focused on Engineering Intelligence to help us do it.
This role sits at the intersection of engineering, data, and operational excellence. Your mission is to transform engineering signals into insights that help us improve software quality, productivity, reliability, and cost efficiency.
You will analyze data from across the software development lifecycle (SDLC), from pull requests and CI/CD pipelines to service reliability metrics and incident management, and translate it into dashboards and insights that guide engineering leaders.
If you are passionate about understanding how engineering organizations work and how they can improve, this role is for you.
What You’ll Work On:
Engineering Effectiveness & SDLC Metrics
You will help measure and improve how our engineering organization builds and operates software. Examples of metrics you will analyze include:
- Development & productivity
- Pull request volume and cycle time
- Code review latency
- Deployment frequency
- Lead time for changes
- Change failure rate
- Reliability & operations
- SLO / SLA performance
- Incident and escalation patterns
- Engineering quality
- Defect trends
- Incident root causes
- Platform adoption
- Usage of internal platforms and services
- Adoption of engineering standards and best practices
- Engineering cost efficiency
- Infrastructure cost trends
- Cost per service / team
- Efficiency of engineering investments
Build Data Products for Engineering
You will create data products used daily by engineering leaders, including:
- Engineering health dashboards
- Service reliability dashboards
- Operational insights for engineering managers
- Executive views of engineering performance
- Adoption dashboards for internal platforms
Dashboards will primarily be built using Superset.
Data Pipelines & Analysis
You will work directly with engineering data systems. Responsibilities include:
- Writing advanced SQL queries to analyze engineering data
- Building lightweight Python pipelines to aggregate and process signals
- Integrating data from sources such as:
- Git repositories (PRs, commits)
- CI/CD systems
- Incident management systems
- Observability platforms
- Ticketing systems
- Cost management tools
You will help ensure that engineering metrics are accurate, consistent, and trusted across the organization.
Generate Insights That Drive Decisions
Beyond dashboards, your work will focus on finding meaningful patterns in engineering data. Examples include:
- Identifying bottlenecks in the development process
- Detecting reliability risks early
- Understanding operational load across teams
- Measuring whether internal platform investments are working
- Connecting engineering activity with infrastructure costs
You will translate complex datasets into clear insights and recommendations for engineering leadership.
Collaborate Across Engineering
This role requires deep collaboration with engineering teams. You will work closely with:
- Engineering managers
- Platform and infrastructure teams
- DevOps / SRE
- FinOps
- Engineering leadership
You will help define consistent engineering KPIs and ensure teams are producing the right operational data.
Qualifications
Technical Skills
- Strong SQL skills
- Experience using Python for data analysis or pipelines
- Experience building dashboards in Superset, Tableau, Looker, or similar BI tools
- Experience working with complex operational datasets
- Familiarity with data modeling and metric definitions
Engineering Awareness
You should be comfortable working with engineering concepts such as:
- Pull Requests (PRs)
- CI/CD pipelines
- Software Development Lifecycle (SDLC)
- Service Level Objectives (SLOs)
- Incident management
- Escalation tickets
- Service reliability metrics
You don’t need to be a software engineer, but you should enjoy working closely with engineers and understanding how systems are built and operated.
Analytical & Communication Skills
- Strong analytical thinking
- Ability to translate ambiguous questions into measurable metrics
- Ability to communicate insights clearly to technical and leadership audiences
- Strong attention to data quality and metric consistency
What Success Looks Like:
Within your first months:
- Engineering leaders have clear dashboards showing service health and engineering productivity
- Reliable metrics exist for SDLC performance and operational health
- Engineering leadership can easily track reliability, quality, and adoption of platforms
Over time:
- Engineering decisions become data-driven
- Operational risks are surfaced early through metrics
- Platform investments can be evaluated through measurable adoption
- The organization develops a shared understanding of engineering effectiveness
Why This Role Is Exciting:
Engineering organizations generate enormous amounts of operational data — but very few companies truly understand it. This role will help us answer questions like:
- Are we becoming more productive or slower over time?
- Are our systems getting more reliable?
- Are our platform investments paying off?
- Where are engineers spending their time?
- Are we scaling engineering efficiently and sustainably?
You will help build the operating intelligence layer for engineering.
Compensation:
Alteryx is committed to fair, equitable, and transparent compensation. Final compensation is determined by several factors, including but not limited to relevant work experience, education, certifications, skills, and geographic location.
The salary range for this role in the United States is $118,700 - $153,900.
Bonus payouts are based on individual and company performance.
In addition to base pay and bonus eligibility, this role includes clear forms of additional compensation, such as:
- A monthly Connectivity Plus stipend of $150 to support remote work-related expenses
- An annual $200 home office reimbursement
Alteryx offers a comprehensive benefits package designed to support your health, financial security, and overall well-being, including:
- Medical, dental, and vision coverage
- 401(k) with company match
- Paid parental leave, caregiver leave, and flexible time off
- Mental health support and wellness reimbursement
- Career development and education assistance
Interested? Learn more and apply today at alteryx.com/careers!
LI-EM1
LI-REMOTE
Find yourself checking a lot of these boxes but doubting whether you should apply? At Alteryx, we support a growth mindset for our associates through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences.
Benefits & Perks:
Alteryx has amazing benefits for all Associates which can be viewed here.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Alteryx will consider for employment qualified applicants with arrest and conviction records.
This position involves access to software/technology that is subject to U.S. export controls. Any job offer made will be contingent upon the applicant’s capacity to serve in compliance with U.S. export controls.
See all 390+ Insights Analyst jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Insights Analyst roles.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an Insights Analyst
Map your degree to the role
H-1B approval for Insights Analyst positions turns on whether your degree field directly aligns with the role. A statistics, economics, or data science degree strengthens your case. A general business degree may trigger an RFE without strong coursework documentation.
Look up prevailing wage tiers before negotiating
Your employer must pay at least the DOL prevailing wage for your location and job level. Use the OFLC Wage Search to check Level I through Level IV wage tiers for Insights Analyst roles before you enter offer negotiations.
Target employers with LCA filing history
Filter your job search to companies that have already filed Labor Condition Applications for analytics roles. Migrate Mate surfaces verified H-1B filing history by employer and occupation, so you can focus on sponsors with a proven track record.
Verify the specialty occupation framing in your offer letter
Your offer letter and job description must frame the Insights Analyst role as requiring a specific degree, not just preferring one. Vague language like 'bachelor's preferred' in official documents has caused USCIS RFEs even when the employer intended to sponsor.
Check your employer's E-Verify enrollment status
USCIS requires H-1B employers to use E-Verify. Confirm your prospective employer is enrolled before accepting an offer. An employer that isn't enrolled cannot legally file your H-1B petition, regardless of their stated intent to sponsor.
Insights Analyst jobs are hiring across the US. Find yours.
Find Insights Analyst JobsInsights Analyst H-1B Visa: Frequently Asked Questions
Does an Insights Analyst role qualify as a specialty occupation for H-1B purposes?
Yes, provided the position requires at least a bachelor's degree in a directly related field such as statistics, data science, economics, or business analytics. USCIS evaluates the job duties and the degree requirement together. Roles where any bachelor's degree is acceptable, regardless of field, are more likely to face an RFE challenging specialty occupation status.
Which industries sponsor H-1B visas for Insights Analyst positions most regularly?
Technology, financial services, healthcare, consumer goods, and market research firms consistently file H-1B petitions for Insights Analyst roles. These industries rely heavily on structured data interpretation, which aligns well with the specialty occupation standard. You can browse open H-1B-sponsored Insights Analyst roles filtered by employer filing history on Migrate Mate.
How does the H-1B cap lottery affect Insights Analyst applicants?
Most private-sector Insights Analyst positions fall under the annual H-1B cap, which covers 65,000 regular-cap slots plus 20,000 slots reserved for U.S. master's degree holders. Registration opens each March and USCIS selects petitions by lottery if demand exceeds the cap, which it has every recent fiscal year. Cap-exempt employers such as universities and certain nonprofits can file outside the lottery window.
What documentation strengthens an H-1B petition for an Insights Analyst?
Your employer's petition should include a detailed job description linking specific duties to your degree field, your official transcripts, and any relevant credentials such as certifications in SQL, Python, or analytics platforms. If your degree title doesn't match the role precisely, a credential evaluation from a NACES-member organization and a letter from an expert in the field can help establish the connection for USCIS.
Can an Insights Analyst on H-1B change employers mid-status?
Yes. Under H-1B portability rules established by the American Competitiveness in the 21st Century Act, or AC21, you can start working for a new employer as soon as they file a non-frivolous H-1B transfer petition, without waiting for approval, as long as your current H-1B has been approved for at least 180 days. The new employer must file before your current authorized stay expires.
See which Insights Analyst employers are hiring and sponsoring visas right now.
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