Data Engineer – Human Capital
GaP Solutions
AWSEC2ETLPythonSQL
Director of Data Engineering
SimplePractice
full-time
Posted on:
Location: 🇺🇸 United States
Visit company websiteSalary
💰 $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
