Senior Data Engineer

About

The Role   As a Senior Data Engineer at Tubi, 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.
As a Senior Data Engineer at Tubi, 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 Tubi’s Growth vertical with the creation and curation of CRM and Growth related pipelines, datasets, and scripting in the Databricks environment and leveraging the Braze CRM platform. Additionally tasks related to general pipeline creation, SQL optimization, data-related automation, and contributing to the strategic direction of data engineering for the Growth organization.

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.
This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week.
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 day time 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
7+ years of industry experience, at least 5 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
Experience building SMS/in‑app/email messaging pipelines at scale (Braze preferred)

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
Pursuant to local pay…