Responsibilities

- Design, develop, and own data pipelines, models, and products supporting Product, Data Science, and GTM functions.
- Manage service-level agreements for data pipelines and full-stack web applications used by internal stakeholders.
- Build and refine data infrastructure, pipelines, tools, data marts, and data services.
- Use Scala, Spark, Airflow, Java, SQL, and Python across the team’s data engineering work.
- Use LLMs and agents at scale to produce high-quality data for ambiguous problems.
- Support GTM forecasting, attainment measurement, product metrics, and strategy-impact analysis.
- Investigate data inconsistencies and resolve deep-rooted data quality issues.
- Collaborate cross-functionally to derive requirements and architect shared datasets.

Requirements





- At least 6 years of experience in a software engineering role focused on building and maintaining data services or data-intensive applications.
- Solid software engineering background and interest in data.
- Experience writing and debugging data pipelines using a distributed data framework such as Spark, Hadoop, or Pig.
- Experience with a backend development language such as Scala, Java, or Go.
- Strong SQL experience.
- Ability to communicate cross-functionally, derive requirements, and architect shared datasets.
- Preferred: experience creating and maintaining data marts for business reporting.
- Preferred: experience working with Product or GTM teams.

📌 Backend Engineer, Data (Toronto)
🏢 Stripe
📍 Toronto