Sr. Data Engineer (On-Site)

About the Role

Key Responsibilities

• Design, develop, and maintain scalable, efficient data pipelines to support ETL/ELT processes across multiple sources and systems
• Partner with Data Science, Analytics, and Business teams to understand data needs, prioritize use cases, and deliver reliable datasets and models
• Monitor, optimize, and troubleshoot data jobs, ensuring high availability and performance of data infrastructure
• Build and manage data models and schemas in Redshift and other data technologies, enabling self-service analytics
• Implement data quality checks, validation rules, and alerting mechanisms to ensure trust in data
• Leverage AWS services like Glue, Lambda, S3, Athena, and EMR to build modular, reusable data solutions
• Drive improvements in data lineage, cataloging, and documentation to ensure transparency and reusability of data assets
• Create and maintain technical documentation and version-controlled workflows (e.g., Git, dbt)
• Contribute to and promote a culture of continuous improvement, mentoring peers and advocating for scalable and modern data practices
• Participate in sprint planning, code reviews, and team retrospectives as part of an Agile development process
• Stay current on industry trends and emerging technologies to identify opportunities for innovation and automation

Requirements

• 6+ years of experience in software/data engineering, with a proven track record of building robust data systems
• Advanced Python skills, including experience building APIs, scripting ETL processes, and automating workflows
• Expertise in SQL, with ability to write complex queries, optimize performance, and work across large datasets
• Hands-on experience with AWS data ecosystem including Redshift, S3, Glue, Athena, EMR, EC2, DynamoDB, Lambda, and Redis
• Strong understanding of data warehousing and data modeling principles (e.g., star/snowflake schema, dimensional modeling)
• Familiarity with dbt Labs and modern ELT/analytics engineering practices
• Experience working with structured, semi-structured, and unstructured data
• Knowledge of data governance, quality assurance, and observability tools to ensure data integrity and trust
• Proficiency in creating technical documentation, SOPs, and maintaining clear communication with cross-functional teams
• A problem-solving mindset, with the ability to take ownership and drive solutions from design to deployment

Nice to Have

• Prior leadership or mentorship experience in data engineering

Qualifications

• Legal right to work in the United States

Benefits & Perks

• Competitive salary
• Industry leading commission opportunities for club employees
• Complimentary Club membership
• Perks and incentives with our products and services including Personal Training, Pilates, Spa and Shop