SimplePractice

Director of Data Engineering

SimplePractice

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $208,000 - $260,000 per year

Job Level

Lead

Tech Stack

AWSAzureCloudGoogle Cloud Platform

About the role

  • Lead, mentor, and grow a high-performing team of data engineers, analytics engineers, and architects
  • Define and execute the data engineering strategy aligned with business goals, in coordination with product engineering and analytics
  • Oversee the design and development of scalable, robust, and secure data pipelines
  • Own and evolve the enterprise data platform (data lake, data warehouse, etc.)
  • Drive best practices in data modeling, architecture, and infrastructure
  • Collaborate with data science, analytics, and application teams to deliver high-quality data products
  • Implement and enforce data governance, quality, security, and compliance standards (e.g., GDPR, HIPAA)
  • Evaluate and implement emerging tools and technologies in the data ecosystem
  • Optimize data storage, processing, and access for performance and cost efficiency
  • Develop and manage the data engineering budget, roadmap, and project priorities
  • Continue to raise the bar on quality, standard and rigor for data practice

Requirements

  • BS and above in Computer Science, Engineering, or a related field.
  • 7+ years of experience in data engineering
  • 3+ years of experience in agile software development
  • Proven leader with experiences in growing and nurturing a team of talent data engineers
  • Proven expertise in building and scaling data platforms in cloud environments (AWS, Azure, or GCP)
  • Strong knowledge of modern data architecture (e.g., lakehouse, data mesh, ELT) and hands-on experience with tools such as Snowflake, dbt, Prefect.
  • Deep Experience with data modeling and warehouse architecture
  • Experience with data governance frameworks and data privacy regulations.
  • Proven experience in aligning multiple functions and stakeholders on technical design choices and strategy
  • Experience working in a product-led or fast-paced startup environment
  • Comfort with ambiguity and able to make decisions with the best information available
  • Familiarity with ML pipelines and support for data science workflows