Analytics Engineer Jobs at Spotify with Visa Sponsorship
Spotify's Analytics Engineer roles sit at the intersection of data infrastructure and product insight, supporting music streaming decisions at scale. Spotify has a consistent track record of sponsoring work visas for this function, and the company navigates the H-1B process with an established internal immigration workflow.
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Get Access To All JobsINTRODUCTION
The Personalization (PZN) team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts and audiobooks better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix.
Our team’s mission is to bring emerging search and agentic experiences to a mature state: exploring, defining, building, validating and optimizing new ideas. These can include new content types in our Search engine or emerging user interaction patterns.
ROLE AND RESPONSIBILITIES
- Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development.
- Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems.
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
BASIC QUALIFICATIONS
Who You Are
- You have a background in machine learning, enjoy applying theory to develop real-world applications, with experience in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
- You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
- You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS.
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
LOCATION
We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.
This team operates within the Eastern Standard time zone for collaboration.
COMPENSATION
The United States base range for this position is $170,000 - $212,000 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.
EEO STATEMENT
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
OUR GLOBAL BENEFITS
- Extensive learning opportunities, through our dedicated team, GreenHouse.
- Flexible share incentives letting you choose how you share in our success.
- Global parental leave, six months off - for all new parents.
- All The Feels, our employee assistance program and self-care hub.
- Flexible public holidays, swap days off according to your values and beliefs.
INTRODUCTION
The Personalization (PZN) team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts and audiobooks better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix.
Our team’s mission is to bring emerging search and agentic experiences to a mature state: exploring, defining, building, validating and optimizing new ideas. These can include new content types in our Search engine or emerging user interaction patterns.
ROLE AND RESPONSIBILITIES
- Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development.
- Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems.
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
BASIC QUALIFICATIONS
Who You Are
- You have a background in machine learning, enjoy applying theory to develop real-world applications, with experience in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
- You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
- You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS.
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
LOCATION
We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.
This team operates within the Eastern Standard time zone for collaboration.
COMPENSATION
The United States base range for this position is $170,000 - $212,000 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.
EEO STATEMENT
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
OUR GLOBAL BENEFITS
- Extensive learning opportunities, through our dedicated team, GreenHouse.
- Flexible share incentives letting you choose how you share in our success.
- Global parental leave, six months off - for all new parents.
- All The Feels, our employee assistance program and self-care hub.
- Flexible public holidays, swap days off according to your values and beliefs.
See all 31+ Analytics Engineer at Spotify jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Analytics Engineer at Spotify roles.
Get Access To All JobsTips for Finding Analytics Engineer Jobs at Spotify Jobs
Frame Your dbt and Spark Skills Clearly
Spotify's Analytics Engineering stack centers on tools like dbt, Spark, and BigQuery. Before applying, align your resume to reflect hands-on experience with these specifically, not just general SQL or ETL work. Vague credentials slow down specialty occupation determinations.
Target Roles in Growth or Personalization Teams
Spotify's Analytics Engineering openings cluster around product areas like personalization, listener growth, and podcast analytics. Applying to roles tied to these verticals signals direct fit and puts you in front of hiring managers who regularly work with sponsored employees.
Understand Spotify's Internal Immigration Workflow
Spotify handles H-1B filings through dedicated immigration counsel, not ad hoc. Once you have an offer, the process moves quickly in Q1 ahead of the April lottery. Confirm your timeline with your recruiter early so USCIS filing deadlines don't create gaps in your work authorization.
Prepare Your Degree Equivalency Documentation Early
If your degree is from a non-U.S. institution or a three-year program, get a credential evaluation from a NACES-approved provider before your offer stage. USCIS scrutinizes foreign degree equivalency for specialty occupation petitions, and delays here can push your start date.
Use Migrate Mate to Identify Active Openings
Spotify posts Analytics Engineer roles across multiple teams simultaneously, and not all are equally open to sponsorship. Use Migrate Mate to filter for Spotify roles verified for visa sponsorship so you're applying where the pathway is confirmed, not guessing from a generic job listing.
Clarify Green Card Sponsorship Intentions During Negotiation
Spotify sponsors both H-1B transfers and PERM-based Green Card processes for Analytics Engineers in qualifying roles. During offer negotiation, ask directly whether the position is eligible for PERM sponsorship, this affects your long-term planning significantly, especially if you're already in the H-1B lottery cycle.
Analytics Engineer at Spotify jobs are hiring across the US. Find yours.
Find Analytics Engineer at Spotify JobsFrequently Asked Questions
Does Spotify sponsor H-1B visas for Analytics Engineers?
Yes, Spotify sponsors H-1B visas for Analytics Engineer roles. The company has an established immigration process and works with outside counsel to manage H-1B filings. Sponsorship is most common for roles in product analytics, data platform, and personalization teams. If you're applying from outside the U.S. or transferring status, confirm sponsorship eligibility directly with your recruiter early in the process.
How do I apply for Analytics Engineer jobs at Spotify?
Apply through Spotify's careers page or use Migrate Mate to browse verified Analytics Engineer openings at Spotify that are confirmed for visa sponsorship. Tailor your application to reflect experience with Spotify's known stack, including dbt, BigQuery, and Spark. Spotify's hiring process typically involves a recruiter screen, a technical assessment, and multiple rounds of structured interviews focused on data modeling and cross-functional collaboration.
Which visa types does Spotify commonly use for Analytics Engineers?
Spotify primarily uses the H-1B visa for Analytics Engineers, which requires a specialty occupation determination tied to your degree and role. For longer-term employees, Spotify also supports employment-based Green Card sponsorship through the EB-2 or EB-3 categories, which involve a PERM labor certification filed with the DOL. The right pathway depends on your qualifications and how long you've been with the company.
What qualifications does Spotify expect for Analytics Engineer roles?
Spotify's Analytics Engineer roles typically require a bachelor's degree or higher in computer science, statistics, mathematics, or a related quantitative field. Strong proficiency in SQL is a baseline expectation, with hands-on experience in data transformation tools like dbt and familiarity with cloud data warehouses such as BigQuery or Snowflake. Experience supporting product teams in a music, media, or subscription business is a meaningful differentiator.
How do I handle the H-1B lottery timeline when targeting a Spotify role?
H-1B registrations open in March and USCIS conducts the lottery shortly after, with an October 1 employment start date for cap-subject petitions. If you're currently on OPT or a STEM OPT extension, confirm your authorization end date lines up with this cycle. If you've already been selected in a prior lottery or hold cap-exempt status, Spotify can file an H-1B transfer with a faster timeline through premium processing.
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