Analytics Engineer - Ads Business Insights

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.

We’re looking for an Analytics Engineer with a history of supplying high quality analytical solutions for data scientists, researchers and business partners. You will supply to the ongoing development of an analysis-first data ecosystem to support the data scientists working for the Spotify Advertising Business Insights (ABI) Team.

In collaboration with a team of data scientists, you will help empower data-driven decision-making across business strategy, sales, operations and marketing functions of the Ads Business.

The Analytics Engineer will sit within the data science team and focus on defining and bringing our vision for our data environment to life. This involves discovering needs for data partners, architecting solutions, and building infrastructure to transform raw data into high-value data assets that support those needs. Building these assets will be key in driving our mission to build word class monetization services for podcast creators.

As part of the Advertising Business team, you’ll work on the latest advertising technologies to connect millions of brands to billions of fans. We’re paving the way for a sustainable global Spotify business that allows even more creators to make a living off their art. Come join us and help build the business team that empowers this!

What You'll Do

• Work closely with Data Scientists to identify upcoming data needs and enhance existing datasets, models and 3rd party data injections or build new ones to fill those needs
• Serve as a data steward and subject-matter guide for a dedicated set of business and technology data domains.
• Develop tools and standard processes to ensure high data quality and identify and prevent errors before they reach production datasets
• Supply to the development of the insights function and the wider analytics and data science community at Spotify
• Operate at the intersection of upstream data producers and consumers, collaborating to define successful analytical outcomes.
• Supply to comprehensive documentation of tools and datasets
• Collaborate with, and mentor, data scientists in building scalable analyses and datasets
• Work as part of a multi-functional team of data scientists, research economists and product managers to build, maintain and support an ecosystem of analysis-friendly datasets, dashboards, and predictive model pipelines.

Who You Are

• Strong proficiency with SQL dialects on distributed or data lake style systems (Presto, BigQuery, Spark/Hive SQL, etc), including SQL-based experience in nested data structure manipulation, windowing functions, query optimization, data partitioning techniques, etc. Knowledge of Google BigQuery optimization is a plus.
• Demonstrated ability in a similar role analyzing large scale data, using both SQL and Python, in a professional setting
• Experience in conducting ETL / ELT with very large and complicated datasets and handling DAG data dependencies.
• You are a communicative person who values building strong relationships with colleagues and partners, enjoys mentoring and instructing others and you have the ability to explain complex topics in simple terms
• You have experience in efficiently building, publishing & maintaining robust data models & warehouses for self serve querying, advanced data science & ML usecases analytics purposes
• Significant experience with dbt (or similar tools), Spark-based(or similar) data pipelines
• Consistent track record of supplying analytics solutions for existing teams, with ability to take open ended goals and scope them into defined and impactful objectives.
• Familiarity general-purpose programming (e.g. Python, Java, Go), dealing with a variety of data structures, algorithms, and serialization formats
• Experience in schema design and data modeling strategies (e.g. dimensional modeling, data vault, etc)
• You will be one of the few AEs supporting a team of data scientists who work on diverse problems. You are a proactive and independent individual contributor who can take inputs from different collaborators and is able to prioritize what’s most important and impactful for the business.
• Familiarity with ad tech and B2B sales is an added bonus for this role
• General knowledge of Jinja templating in Python. Hands-on experience with cloud provider integration and automation via CLIs and APIs.

Where You'll Be

• Where in the world? For this role, it can be within North America, and we operate within Eastern time zone hours.
• We are a distributed workforce enabling our band members to find a work mode that is best for them.
• Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.

The United States base range for this position is $115,702-$144,628 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, 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.

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.