Manager of Data Engineering

Summary

Join StyleSeat as a Manager of Data Engineering to lead and contribute to our data strategy and engineering practices. You will manage a team of Data & BI Engineers, balancing individual contributor work while crafting and executing a technical vision. Collaborate with Data Scientists, Analysts, and Product Managers to make data-driven decisions and create data-driven product experiences. This role requires technical excellence and a passion for understanding the StyleSeat marketplace and its impact. Translate business challenges into technical solutions, connecting data architecture decisions to business outcomes. Inspire your team to create tangible value beyond elegant infrastructure. The ideal candidate will have 5+ years of data engineering experience and 1+ year of team lead/people management experience.

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