Data Engineer, Core Data Engineering

About the Role:

As a Data Engineer, you'll be instrumental in developing and maintaining robust data processing pipelines that underpin our reporting, analytics, and performance insights. You'll operate as an embedded data engineer within a specific data product vertical, shaping the culture, best practices, and overall approach to data engineering within the team. Our diverse product verticals, such as Viewer Growth, Ad Product Sales, and Marketing Analytics, are all highly data-driven.

In this role, you will also be responsible for supporting your vertical with data-related automation, mentoring junior engineers if need be, and contributing to the strategic direction of data engineering across the company. Each product team presents unique big data challenges, requiring you to be adaptable, curious, and possess a strong foundation in big data and engineering principles. Your responsibilities will span from constructing efficient pipelines and facilitating data access for data scientists and analysts to building specialized data products that empower non-engineering teams with deeper insights into their datasets.

What You'll Do:

• Be the primary owner of the data needs of a specific product vertical. That means everything from raw-data ingestion to end-user analysis.
• Build intuitive, easy-to-use, and high-quality datasets using Spark and DBT.
• Track down data quality issues when they arise, and then set appropriate data quality monitors and alerts to help prevent future incidents.
• Participate in the occasional on-call rotation (12-hr shifts, ~1-2/month).
• Understand your product vertical's datasets, with an ability to document and educate your team on how certain tables/fields are meant to be used.
• Be the liaison between your product vertical and the core data infrastructure team to make sure business needs are met in a computationally efficient manner.

Your Background:

• BSc/MSc in Computer Science or related field.
• 4+ years of industry experience, at least 3 of which are in a data engineering (or data-centric software engineering) role.
• Track record of building and operating scalable, flexible, and always-on data pipelines.
• A desire and ability to truly understand and serve the business problems and use-cases you will be working with.
• Fluent in data manipulation and SQL.
• Strong knowledge of Spark, Python (libraries like pandas and polars, helpful).
• Strong experience with Databricks (SQL Warehouses, Jobs Clusters, and Serverless).
• Familiarity with DBT and Airflow in particular is helpful.
• Experience with cloud providers and cloud storage (AWS preferred).
• Experience with efficiently working with datasets at TB scale.
• Service and data quality oriented.
• A passion for shipping production quality code with good test coverage.
• Ability to prioritize tasks and self-motivate without constant supervision.