Backend engineer /Machine learning

We sell products like Marquee and Showcase via Spotify for Artists, helping artists reach listeners across the Spotify consumer app. Behind these formats is a sophisticated ecosystem of forecasting, targeting, supply optimization, and campaign delivery infrastructure that powers millions of promotional campaigns. We are looking for a Backend Engineer II with strong data engineering skills to join the OptiMyst squad within the Native Ads Performance pillar. enabling us to meet customer demand and performance goals. Our squad sits at the intersection of backend systems and data-intensive ML infrastructure. Design, build, and operate backend services and large-scale data pipelines that power Native Ads forecasting, supply allocation, and campaign delivery optimization. Develop and maintain the data infrastructure behind ML forecasting models that predict campaign reach, clicks, conversions, and supply availability across segments, surfaces, and markets. supporting bulk buying workflows, multi-subcampaign budget allocation, and high-throughput forecast serving for internal and external customers. Collaborate with data scientists and ML engineers to productionize prediction models, build feature pipelines, and ensure model outputs are reliable and observable in production. Help drive improvements to data quality, pipeline reliability, and system observability across the forecasting and delivery stack. Work in a cross-functional, agile squad alongside product managers, data scientists, and other engineers to continuously experiment, iterate, and deliver on squad objectives. You have 3+ years of professional experience in backend engineering, with meaningful exposure to data engineering or ML infrastructure. You are proficient in at least one backend language such as Java, Scala, or Python, and have experience building services and data pipelines that operate at scale. You have experience with distributed data processing frameworks (e.g., You are familiar with cloud data platforms, ideally GCP, including tools like BigQuery, Cloud Storage, Pub/Sub, and Dataflow. You understand data modeling, pipeline orchestration, and the tradeoffs between batch and streaming architectures. You care about data quality, system reliability, and building infrastructure that downstream consumers, whether ML models, product surfaces, or business stakeholders, can trust. You are excited to work at the boundary of backend systems and data/ML, and are eager to deepen your skills in both areas. The United States base range for this position is $125,300 - $179,000 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. Placement in a level depends on relevant work history and interview performance. 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. 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. 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.