Senior Data Engineer

About Restore Hyper Wellness

Restore Hyper Wellness is the award-winning creator of Hyper Wellness—a revolutionary new category in health. With over 200 studios across 40 states, we deliver innovative, science-backed therapies that empower our clients to look and feel their best. By joining Restore, you’re part of a movement dedicated to expanding the limits of personal potential and performance to help people do more of what they love.

Why Join Us?

• Pioneering Wellness: Be a part of an industry-leading company at the forefront of wellness innovation.
• Impactful Work: Your contributions will directly influence the quality of care and service our clients receive, making a tangible difference every day.
• Innovation and Collaboration: Work in a dynamic environment where you’ll collaborate across multiple departments, contributing to a comprehensive wellness strategy.
• Commitment to Employee Wellness: Enjoy complimentary access to Restore’s cutting-edge therapies, including onsite services at our Austin Headquarters office.
• Growth and Development: Access opportunities to develop your skills, advance your career, and help shape the future of wellness.
  

Role Overview

Job Title: Sr. Data Engineer
Location: Austin, TX HQ or remote
Department: PTD (Product, Tech, Data)
Reports to: Director Data Analytics
Job Type: Full-Time, Exempt

Please note: While Restore is able to transfer a current H-1B visa, we are unable to support sponsorship for a new H-1B visa.

We are seeking a highly skilled and experienced Sr. Data Engineer to join our team. As a Data Engineer, you will be instrumental in designing, developing, and maintaining our robust data infrastructure. You will collaborate with various departments to develop requirements and ensure the smooth flow of data throughout the organization which will enable us to make data-informed decisions and deliver best in class services to our clients.

Key Responsibilities

• Define and implement the overall data strategy, ensuring alignment with business objectives and accounting for current OKRs.
• Design and implement data models that meet both functional requirements.
• Develop and maintain data integration processes, ensuring seamless data flow between systems.
• Establish and enforce data quality standards and governance policies to ensure data integrity and compliance.
• Monitor data pipelines, infrastructure components, and data processing jobs to identify and resolve performance issues.
• Recommend and optimize system configurations, database queries, and data processing algorithms for improved performance.
• Use performance monitoring tools and techniques to proactively address any issues and ensure optimal performance.
• Evaluate and recommend new data technologies and tools that can improve data architecture.
• Ensure data security and privacy by implementing robust data protection measures.
• Design systems to handle increasing amounts of data efficiently and ensure high performance and reliability.
• Maintain comprehensive documentation of data architecture, models, and processes, and establish standards for data management.
• Build efficient and reliable data pipelines using tools such as BigQuery, DBT, Apache Airflow, Terraform or similar frameworks.
• Extract, transform, and load data from various sources into data warehouses or data lakes. Implement data quality checks, data validation, and error handling mechanisms to ensure data integrity and accuracy.
• Implement data governance best practices and ensure data security and compliance with relevant regulations. Define access controls, data retention policies, and data privacy measures to protect sensitive data. Work closely with the security and compliance teams to address any data-related concerns.
• Work closely with cross-functional teams, including analysts, and software engineers, to understand data requirements and provide data engineering support. Share knowledge and best practices with team members to foster a culture of learning and continuous improvement.

Requirements

Education:

• Bachelor’s degree in a related field or equivalent experience.

Experience:

• 3-5 years of experience as a Data Engineer, Data scientist, or similar role.

Skills:

• Proficiency in SQL and cloud-based data platforms with emphasis in GCP or AWS.
• Strong programming skills in SQL and Python. Experience with R preferred, but not required.
• In-depth knowledge and familiarity with VCS such as GitHub.
• Proficiency in Airflow for orchestration and workflow management.
• Experience with DBT (Data Build Tool) or similar data transformation frameworks.
• Familiarity with data governance, data security, and privacy best practices.
• Understanding of data modeling, database design, and query optimization techniques.
• Proficiency in data visualization tools such as Tableau, Power BI, or similar.
• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication and collaboration skills with the ability to self-manage.
• Ability to handle multiple projects and prioritize tasks in a fast-paced environment.
• Experience with LLMs and machine learning concepts will be considered a strong plus.
• Experience with CI/CD and Docker Deployments
• Familiarity with Terraform or IAC(infrastructure as Code) practices.

Certifications/Licenses:

• Certification in GCP or AWS preferred, but not required.

Benefits

• A competitive salary plus annual bonus based on company performance.
• Medical, dental and vision benefits effective within 30 days of hire.
• 401k matching up to 4%.
• Flexible PTO.
• Casual dress code. 
• Fun, wellness-focused work environment.
• Complementary and discounted therapies in-studio and in-office

Restore Hyper Wellness is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.