Director of Data Engineering

at Aspen Dental in Chicago, Illinois, United States

Job Description

The Aspen Group (TAG) is one of the largest and most trusted retail healthcare business support organizations in the U.S. and has supported over 16,000 healthcare professionals and team members at more than 1,200 health and wellness offices across 46 states in four distinct categories: Dental care, urgent care, medical aesthetics, and animal health. Working in partnership with independent practice owners and clinicians, the team is united by a single purpose: to prove that healthcare can be better and smarter for everyone. TAG provides a comprehensive suite of centralized business support services that power the impact of five consumer-facing businesses: Aspen Dental, ClearChoice Dental Implant Centers, WellNow Urgent Care, Chapter Aesthetic Studio, and AZPetVet. Each brand has access to a deep community of experts, tools and resources to grow their practices, and an unwavering commitment to delivering high-quality consumer healthcare experiences at scale.

The Aspen Group (TAG) is seeking a highly skilled and experienced Director of Data Engineering to lead our data engineering team. This role requires a strategic thinker who can provide mentorship, ensure the highest standards of data quality and code quality, and collaborate with business partners across TAG’s diverse brands to solve complex data challenges. The ideal candidate will be adept at both leadership and hands-on technical skills, ensuring that our data infrastructure is robust, scalable, and efficient.

Key Responsibilities:

Mentorship & Team Development

+ Provide mentorship and professional development opportunities for team members.

+ Foster a collaborative and inclusive team environment.

+ Conduct regular performance reviews and provide constructive feedback.

Scrum Master Responsibilities:

+ Act as the Scrum Master for the data engineering team.

+ Facilitate daily stand-ups, sprint planning, backlog grooming, and retrospectives.

+ Ensure the team follows Agile best practices and continuously improves processes.

Collaboration with Business Partners:

+ Work closely with business partners across TAG brands to understand their data challenges.

+ Provide guidance and solutions to meet business needs.

+ Translate business requirements into technical specifications and actionable tasks for the team.

Ensuring Quality and Adherence to Definition of Done:

+ Establish and enforce standards for data quality, code quality, and unit testing.

+ Ensure the team adheres to the definition of done, including thorough testing and validation of data pipelines.

+ Implement and maintain tools and processes for linting, continuous integration, and continuous deployment.

Technical Leadership and Innovation:

+ Lead the design and development of scalable data architectures and pipelines.

+ Stay up to date with the latest industry trends and technologies and integrate them into TAG’s data strategy.

+ Oversee the implementation and maintenance of data governance and security best practices in conjunction with the Data Governance Team

Tooling and Technologies:

+ Manage and optimize the use of data engineering tools and platforms including:

+ JIRA for project management and Agile processes.

+ Cloud Composer (Airflow) for workflow orchestration.

+ Python for data processing and automation.

+ Dataflow for stream and batch processing.

+ Pub sub for messaging and event ingestion.

+ Big Query for data warehousing and analytics.

+ DBT Cloud for data transformations and modeling.

+ Monte Carlo for data observability and reliability.

+ Evaluate and integrate additional tools as needed to support evolving business needs.

Performance Monitoring and Optimization:

+ Implement monitoring and alerting systems to ensure data pipelines and processes are reliable and performant.

+ Proactively identify and resolve performance bottlenecks and data quality issues.

+ Optimize resource usage and cost efficiency of data infrastructure.

Qualifications:

+ Bachelor’s or master’s degree in computer science, Data Engineering, or a related field.

+ 10+ years of experience in data engineering or a related field, with at least 5 years in a leadership role.

+ Proven experience with the tools and technologies listed above.

+ Strong understanding of data architecture, ETL processes, and data governance.

+ Excellent communication and interpersonal skills.

+ Ability to work in a fast-paced, dynamic environment and manage multiple priorities.

+ Strong problem-solving skills and attention to detail.

Salary: $200,000-270,000/year + 25% performance bonus