Director, Data Engineering - Lyra Health

Job Title: Director, Data Engineering
Job Location: United States
Job Listing URL: https://jobs.lever.co/lyrahealth/3545c42e-7f77-43af-8598-905c1555d643
Job Description: About Lyra Health

Lyra Health is the leading provider of mental health solutions for employers supporting more than 20 million people globally. The company has delivered 13 million sessions of mental health care, published more than 20 peer-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness and cost efficiency. Extensive peer-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life-changing mental health care through Lyra Empower, the only fully integrated, AI-powered platform combining the highest-quality care and technology solutions.

About the Role:
We are seeking a visionary and results-oriented Director, Data Engineering to lead and scale our growing team of talented data engineers. In this critical leadership role, you will be responsible for driving the strategy, implementation, and deployment of cutting-edge data solutions across our core data infrastructure for internal and external stakeholders. You will play a pivotal role in shaping the future of our data warehouse, data pipelines, data sharing, data integration, BI tooling, and delivering significant business value through the innovative application of modern data technologies.

Lyra is for you if you:
- Want to work with brilliant people solving hard problems
- Have a passion for social impact and helping people when they are most vulnerable
- Enjoy collaborating across teams with data scientists, analysts, operations and product managers.

Responsibilities
Be a hands-on technical visionary leader for the data engineering team responsible for solutioning, designing, implementing, reviewing, and deploying core functionality to support our data warehouse, data pipelines, data sharing, data integration and BI tools strategy.
Manage, scale, and mentor the data engineering team along with leading the recruitment efforts to attract and retain top data engineering talent.
Collaborate with stakeholders to prioritize top business initiatives and develop corresponding solutions and a strategic roadmap.
Identify and evaluate emerging data engineering technologies and trends, and determine their potential application within the organization.
Manage resource allocation and bi-weekly sprint planning.
Advocate for and drive the adoption of best practices in data engineering development, deployment, and data governance.
Work closely with the data science, analytics, and operations teams to develop user-friendly data solutions that comply with established data governance guidelines.
Qualifications
5+ years working as an engineering lead/manager focused on data engineering and implementation of a modern data stack strategy in a large scale environment.
A track record of leading and scaling data engineering teams
Experience architecting robust, fault-tolerant data pipelines with solid logging, alerting, and data validation—not just simple scripts
Hands-on experience designing and implementing data warehouses using modern cloud databases like Snowflake, BigQuery, or Databricks
Hands-on experience in SQL-based data modeling with a focus on governance and enabling self serve using a development framework such as DBT
Experience implementing integration Platform as a Service (iPaaS) solutions like Workato, Mulesoft, or Talend.
Experience with data visualization tools such as Tableau, Looker or Sigma
Experience working with sensitive data in a healthcare or similarly regulated environment
A thoughtful approach to balancing quality and deadlines in fast-paced settings
Excellent communication skills with a talent for building consensus and alignment
Strong communication skills and ability to generate consensus and buy-in within cross team and stakeholders
Organizational skills and the ability to simplify complex problems and prioritize what matters most for the sake of the team and the business.