Skip to content

Analytics Engineer - Ads Business Insights

Spotify LogoSpotify
View Organization

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 Biz.

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 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.
  • 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
  • Collaborate with, and mentor, data scientists in building scalable analyses and datasets
  • Develop tools and standard processes to ensure high data quality and identify and prevent errors before they reach production datasets
  • Serve as a data steward and subject-matter guide for a dedicated set of business and technology data domains.
  • Supply to comprehensive documentation of tools and datasets
  • Operate at the intersection of upstream data producers and consumers, collaborating to define successful analytical outcomes.
  • Supply to the development of the insights function and the wider analytics and data science community at Spotify

Who You Are

  • Demonstrated ability in a similar role analyzing large scale data, using both SQL and Python, in a professional setting
  • 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.
  • 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
  • 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
  • Experience in conducting ETL / ELT with very large and complicated datasets and handling DAG data dependencies.
  • 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.
  • Experience in schema design and data modeling strategies (e.g. dimensional modeling, data vault, etc)
  • Significant experience with dbt (or similar tools), Spark-based(or similar) data pipelines
  • Familiarity general-purpose programming (e.g. Python, Java, Go), dealing with a variety of data structures, algorithms, and serialization formats
  • General knowledge of Jinja templating in Python. Hands-on experience with cloud provider integration and automation via CLIs and APIs.

The United States base range for this position is $115,702-$144,628 plus equity, plus bonus or commission.

‌