Manager of Data Engineering

Summary

Join StyleSeat as a Manager of Data Engineering to lead and contribute to the data strategy and engineering practice. Manage a team of Data & BI Engineers while also contributing individually. Craft and execute a technical vision to enable data-driven decisions and product experiences. Collaborate with Data Scientists, Analysts, and Product Managers. This role requires technical excellence and a passion for understanding the StyleSeat marketplace and its impact. Translate business challenges into technical solutions and inspire the team to create tangible value. The ideal candidate will have a strong background in data engineering and team leadership.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

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