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The Role
Own the technical infrastructure supporting Spotify’s revenue growth programs. Build and maintain dbt models, BigQuery pipelines, dashboards, reports, and LLM-enabled data workflows. Monitor pipeline health, resolve data issues with engineering and Insights teams, and translate sales needs into reliable data products that improve prioritization, outreach, and advertiser growth.
Summary Generated by Built In
Sell what you love. For us and millions of users across the globe, that’s Spotify. Join the Sales team and you’ll build the relationships that help grow our business in existing markets and beyond. We don’t just sell creative solutions to our clients and partners, we help to shape them; using our expert knowledge of ad products, sales channels and the industry to impact the way the world experiences music and podcasts.
Our Revenue Growth team drives advertiser acquisition and retention at scale by turning data into action. We build and run scalable go-to-market programs that help advertisers succeed, through lifecycle communications and seller-facing actions.
As a Senior Program Analyst - GTM Ops, you'll own the technical layer that makes Revenue Growth actually run. Working within Spotify's broader data infrastructure, you'll build the team-specific tools, endpoints, and pipelines our programs depend on — the reporting that helps sellers act, the data feeds that power our advertiser tools, the pipelines that keep everything moving. Your work won't be abstract; it shows up directly in what the team ships and what sellers experience.
What You’ll Do
- Work on high-impact data problems that support revenue growth and help our advertising business scale
- Build and maintain dbt models and BigQuery pipelines that power team tools and seller-facing reporting
- Monitor pipeline health, identify issues early, and partner with data engineering and Insights teams to resolve upstream challenges
- Create dashboards and reports that sales teams rely on, translating business needs into clear, actionable views
- Partner closely with sales teams and leadership to understand needs, scope solutions, and deliver data that supports prioritization and decision-making
- Improve how data is used in the sales process by surfacing signals that help teams focus, personalize outreach, and close opportunities
- Support and extend pipelines that process unstructured data using LLMs, ensuring outputs are reliable, validated, and usable within BigQuery
Who You Are
- You have 4+ years of experience in analytics engineering, BI engineering, or data/reporting roles, ideally supporting go-to-market, growth, or sales teams
- You are experienced with SQL and BigQuery, and build with reliability and maintainability in mind
- You have worked with dbt and understand how to extend and maintain models within an existing DAG
- You enjoy building systems that work consistently for a team and take pride in operational reliability
- You communicate clearly and can partner directly with non-technical stakeholders to understand needs and deliver solutions
- You are comfortable translating business questions into structured data outputs and reporting
- You are curious about applying AI in data workflows, including working with or learning about LLM-driven pipelines
Where You’ll Be
- This role is based in New York City.
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
The United States base range for this position is $92,293 - 131,847, 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.
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.
Skills Required
- 4+ years of experience in analytics engineering, BI engineering, or data/reporting roles
- Experience supporting go-to-market, growth, or sales teams
- Experience with SQL and BigQuery
- Experience working with dbt and maintaining models within an existing DAG
- Ability to build reliable and maintainable data systems
- Clear communication and ability to partner with non-technical stakeholders
- Ability to translate business questions into structured data outputs and reporting
- Interest or experience applying AI in data workflows, including LLM-driven pipelines
Spotify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Spotify and has not been reviewed or approved by Spotify.
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Flexible Benefits — Employees consistently praise the total compensation package beyond base salary, highlighting a mix of RSUs, cash incentives, and stipends alongside core pay. The package is described as flexible and customizable through equity choices (e.g., RSUs, options, cash) that can be tailored for long-term wealth building.
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Leave & Time Off Breadth — Time-off offerings are repeatedly highlighted as substantial, including generous vacation, paid sick days, volunteer time, and flexible holidays. These policies are framed as a meaningful part of the overall rewards experience beyond salary.
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Healthcare Strength — Health coverage is portrayed as comprehensive, spanning medical, dental, vision, life insurance, disability coverage, and mental health support. Additional employer contributions to HSAs are cited as strengthening the overall health and wellness value proposition.
Spotify Insights
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The Company
What We Do
Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 50m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience.
