About The Role
EWC is looking for a motivated Senior Data Engineer to join our growing team of data experts. In this role, you will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is an experienced data pipeline builder and engineer who enjoys optimizing data systems and building them from the ground up. The Sr. Data Engineer will support our data analysts/scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
A Day In The Life
As a Senior Data Engineer at European Wax Center, you’ll help shape a modern, cloud-native data platform. Your day-to-day responsibilities will include:
Data Pipeline & Platform Engineering
- Design, build, and maintain scalable data pipelines using tools like dbt and Airflow, ensuring reliable ingestion, transformation, and delivery of data across the organization.
- Architect and optimize batch and streaming data workflows on AWS, leveraging services such as S3, RDS, and Snowflake.
- Assemble and manage large, complex data sets to meet a range of business requirements, while ensuring performance, reliability, and scalability.
- Implement robust monitoring, logging, and alerting for data workflows to ensure pipeline health and minimize downtime.
Collaboration & Business Partnership
- Partner with stakeholders across Operations, FP&A, Supply Chain, and Executive teams to understand data needs, support analytics initiatives, and provide scalable solutions.
- Translate business requirements into technical solutions, collaborating with analysts, data scientists, and BI developers to deliver impactful insights.
- Support cross-functional efforts to improve data accessibility, standardization, and quality.
Data Quality, Governance & Security
- Develop and enforce data validation frameworks and quality checks to ensure accuracy, completeness, and reliability.
- Implement data security best practices to keep sensitive information secure during transmission and at rest, including encryption strategies.
- Maintain and evolve metadata and lineage tracking to support transparency and data stewardship.
Innovation & Continuous Improvement
- Identify and drive process improvements in data delivery, pipeline efficiency, and infrastructure automation.
- Contribute to the evolution of EWC’s data architecture to support emerging business use cases and product innovation.
- Conduct research and troubleshoot issues related to data storage, integration, and performance.
What Sets You Apart
- Proven passion and talent for teaching fellow engineers and non-engineers.
- Strong analytic skills related to working with unstructured datasets.
- Adopts EWC values in personal work behaviors, decision making, contributions and interpersonal interactions.
- Helps shape a positive work environment by demonstrating and influencing others to reward performance and value "can do" people, accountability, diversity and inclusion, flexibility, continuous improvement, collaboration, creativity, and fun.
- Experience with commercial data engineering/science solution initiatives.
- Ability to manage a broad range of deliverables with ambiguous task symptomatology while consistently achieving collaborative success with others to accomplish goals.
- Works well in a team environment and takes pride in participating in projects that employ the skills of all team members.
- Ability to learn quickly in a dynamic environment and to troubleshoot issues.
- Business savvy communications skills and concise written communication skills.
- Ability to be self-sufficient and self-driven in a small team.
- Understanding of the current threat and vulnerability landscape.
- Excellent organization and presentation skills.
Education And Experience
- BS in math, economics, engineering or other technical field preferred; advanced degrees a plus.
- 7+ years of professional software development or data engineering experience.
- 5+ years of SQL experience with dimensional data modeling & schema design in relational data warehouses
- 5+ years of experience in ETL/ELT pipeline design, implementation and maintenance with relational databases
- 5+ years of experience with ETL/ELT tools (ideally dbt and Airflow experience)
- Experience designing, building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- Design and maintain efficient, scalable data pipelines that improve analytics speed and reliability.
- Experience deploying production systems in the cloud (i.e., AWS, Azure).
- Strong communication skills in writing and conversation.
- Experience with tools we use every day:
- Storage: Snowflake, AWS Storage Services (e.g., S3, RDS, Glacier)
- ETL/BI: Astronomer, dbt, Domo, Tableau, PowerBI
- Experience with encryption at rest, including multiple approaches and tradeoffs.
- Strong proficiency in Python for data manipulation and scripting.
- Experience in Retail operations.
European Wax Center is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. This job description is a general description of essential job functions. It is not intended to describe all duties someone in this position may perform. All employees of EWC and operating subsidiaries are expected to perform tasks as assigned by supervisory/management personnel, regardless of job title or routine job duties.
