Candidates should possess a BSc/MSc in Computer Science or a related field, with at least 7 years of industry experience, including 5 years in a data engineering or data-centric software engineering role. A strong track record of building and operating scalable data pipelines for product experimentation and Data Science needs is required, along with fluency in data manipulation and SQL. Strong knowledge of Spark, Python (including pandas and polars), Databricks, DBT, Airflow, and cloud providers (AWS preferred) is essential. Experience with TB-scale datasets, a service and data quality orientation, and a passion for shipping production-quality code with good test coverage are also necessary. Familiarity with the StatSig product development tool is preferred.
The Senior Data Engineer will be the primary owner of a specific product vertical's data needs, building high-quality datasets using Spark and DBT, and tracking down data quality issues while setting up monitors and alerts. Responsibilities include supporting the vertical with data-related automation, mentoring junior engineers, contributing to the strategic direction of data engineering, and acting as a liaison between the product vertical and core data infrastructure teams. The role involves understanding Data Science and experiment-related datasets, documenting them, and educating the team on their usage, as well as participating in an occasional on-call rotation.
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