Manager of Data Engineering

About the role

We are looking to add a Manager of Data Engineering to lead our Data Engineering team – this is an opportunity for a hands-on technical leader to contribute to our data strategy and engineering practice while managing a talented team of engineers that are at the center of enabling a data-driven organization and product experience.

This team leader will manage a team of Data & BI Engineers while balancing individual contributor work. They will craft and execute a technical vision alongside our Head of Data that enables the company to make data-driven decisions across our business and create data-driven product experiences for our community, collaborating closely with Data Scientists, Analysts, and Product Managers in our broader data organization.

This role is ideal for data engineering leaders who combine technical excellence with a passion for understanding the StyleSeat marketplace, our beauty professional community, and the real-world impact of our product. We're seeking someone who thrives on rapidly translating business challenges into technical solutions, with the insight to connect data architecture decisions directly to business outcomes and the ability to inspire their team toward creating tangible value beyond just elegant infrastructure.

What you'll do

• Craft and execute a technical vision for our data infrastructure and engineering practices, aligning with the overall data team & StyleSeat goals
• Get in the weeds with your team on executing towards that shared vision
• Improve reliability, scalability, and quality of our Analytics/BI infrastructure, dbt instance, and general ETL pipelines
• Improve testing infrastructure by implementing robust CI/CD pipelines, testing frameworks, and quality gates across environments
• Develop and implement real-time event streaming solutions, partnering with our data science teams to deliver algorithms and user experiences to production
• Enhance the team's development processes to increase velocity while maintaining code quality and business impact
• Establish and track predictable metrics to measure development efficiency and data quality
• Develop in Python, SQL (MySQL and Redshift), and work with AWS services including SageMaker
• Implement infrastructure as code using Terraform
• Collaborate with cross-functional teams to ensure data engineering solutions deliver measurable business value
• Hold the team accountable for delivering high-quality solutions that meet business requirements on time

Who you are

Successful candidates can come from a variety of backgrounds, yet here are some of the must have and nice to have experiences we're looking for:

Must Have:

• 5+ years experience in data engineering roles
• 1+ years experience in team lead or people management roles
• Strong desire to get in the weeds with our stakeholders and our community, manage ambiguity, understand their pain points and how data can help solve their problems
• Expert SQL skills with deep experience in both MySQL and Redshift
• Strong understanding of analytics data modeling concepts, testing frameworks, and observability
• Experience with dbt for data transformations
• Experience implementing CI/CD pipelines (preferably CircleCI) and automated testing
• Strong Python proficiency for data pipeline development and testing automation
• Hands-on experience with Airflow and/or Amazon MWAA for workflow orchestration
• Experience with AWS cloud services for DevOps
• Experience with Terraform for infrastructure as code
• Strong understanding of data engineering best practices and driving a data engineering team vision
• Proven leadership skills with ability to drive & get in the weeds on technical initiatives
• Excellent communication skills with ability to work across departments and technical skill levels.

Nice to Have:

• Knowledge of FluentD, Kinesis and other tools for real time data processing streams.
• Experience with Django framework.
• Experience with Tableau or other BI tools for visualizations and reporting
• Experience with implementing self-service analytics platforms for stakeholders
• Experience leading engineering practice improvements across teams
• Data quality monitoring and observability implementation
• Background in test-driven development methodologies

 

Salary Range

Our job titles may span more than one career level. The career level we are targeting for this role has a base pay between $168,000 and $180,000. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business ne