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.
Spotify is searching for a business-focused data engineer that has a passion for data analysis, designing data architectures and data pipelines. You will be joining a team that is dedicated to supporting the growing ads business within Spotify. Your efforts will not only enable better business decisions for leadership, but they’ll also help scale the impact of our data science work.
What You'll Do
- Build pipelines & datasets that’ll enable our better decision making for the ads business. You’ll also build feature pipelines that’ll funnel data into our ML models.
- Design data models & data architectures for our ads business data ecosystem. This may include ads forecasting algorithms, segmentation analysis.
- Integrate pipelines connecting 3rd party API integrations into our data infrastructure.
- Be self driven and self sufficient to be able to craft, prioritize and drive the data engineering roadmap.
- Scale up the data processing of our machine learning models across machines.
- Work in collaboration with scientists, ML experts and data engineers across Analytics to imagine and build creative solutions to challenging questions, most often with a clear line of sight from your work to real-world impact.
- Monitoring & alerting systems for diagnosing and optimizing production pipeline & algorithm jobs.
Who You Are
- You will be successful in this role if you:
- Have a strong vision of how our data engineering practice could evolve within our ads business to not just support our current needs but also the needs of the business team broadly.
- Have 5+ years of experience as a data engineer or analytics engineer.
- Must be familiar with Python, SQL.
- Experience working as a data engineer embedded on a data science team.
- Experience with data orchestration tools like Flyte, Airflow, Luigi, Flo etc. We use Flyte.
- Know how to work with high volume heterogeneous data, preferably with distributed systems such as Hadoop.
- Have some high-level knowledge of how machine learning algorithms work. Bonus points if you’re familiar with productionisation of ML algorithms.
- Knowledgeable or curious about functional data processing with technologies using Spark, Java, Scala etc.
- Comfortable driving your own roadmap and managing the priorities across different data science teams.
- You are skilled at crafting and building robust distributed Microservices with tools like Docker, Kubernetes, AWS ECS/EKS etc.
- You are proficient in object-oriented and/or functional programming languages: Python, Java/Scala, Chef, Terraform
The United States base range for this position is $178,600 -$223,250 plus equity, plus bonus or commission. 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. 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.
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.
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