Phreesia

Senior Director, Data Engineering

Phreesia

full-time

Posted on:

Origin:  • 🇨🇦 Canada

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Job Level

Senior

Tech Stack

CloudETLPythonSQLTableauTensorflow

About the role

  • The Senior Director of Data Engineering is responsible for building a cohesive data organization that fosters collaboration and drives innovation across the entire company.
  • This strategic shift from independent and narrow-focused data teams to a unified organization is one of Phreesia’s top priorities.
  • Inwardly, this role will drive the transformation of multiple teams, including Data Engineering and Data Science, and forging partnerships between the data organization and product engineering.
  • The role will have a significant outward focus on business opportunities, driving value, and enhancing the company’s competitive edge.
  • This is a fully remote position with priority given to candidates in the EST/CST time zones.

Requirements

  • Bachelor's degree required
  • 10+ years of experience in data engineering, with at least 5 years in leadership roles managing teams and managers.
  • Prove n success leading data organizations through modernization efforts and major platform shifts (e.g., cloud migrations, BI platform overhauls).
  • Deep expertise in building and operating modern data platforms (experience with Snowflake strongly preferred).
  • Strong knowledge of data modeling, ETL frameworks, semantic layers, data science techniques, and data governance best practices.
  • Track record of developing and leading high-performing engineering and data science teams and driving cultural change.
  • Exceptional cross-functional collaboration skills with Product Management, Engineering, Data Science, and business stakeholders.
  • Identify areas where Data Science and Data Engineering can create value for Phreesia and advocate on their behalf
  • Experience working with external consulting firms on large-scale initiatives.
  • Passionate about building a quality-first engineering culture and delivering trusted, reliable data solutions.
  • Technology: Cloud based data warehouse technologies, e.g. Snowflake BI Solutions, such as Power BI, Tableau, etc. Data ingestion and transformation tools, e.g. FiveTran, dbt, etc. Data Observability platforms, like Monte Carlo, or BigEye. Deep learning frameworks, such as Tensorflow, CNTK, etc SQL, python, or other languages suitable for data engineering.