Lead Data Engineer

OneOncology is positioning community oncologists to drive the future of medical care through a patient-centric, physician-driven, and technology-powered model to help improve the lives of everyone living with cancer and other diseases. Our team is bringing together leaders to the market place to help drive OneOncology’s mission and vision.

Why join us? This is an exciting time to join OneOncology. Our values-driven culture reflects our startup enthusiasm supported by industry leaders in oncology, urology, technology, and finance. We are looking for talented and highly-motivated individuals who demonstrate a natural desire to improve and build new processes that support the meaningful work of independent physicians and the patients they serve.

Job Description:

OneOncology is seeking a Lead Data Engineer for a full-time role based in Austin, TX, Nashville, TN, or remote. The Lead Data Engineer is a hands-on technical leader who designs, builds, and operates the data pipelines and platform components that power advanced analytics, AI/ML initiatives, and critical business operations. Working closely with data analysts and engineering teams, you will translate business and technical requirements into reliable, scalable, high-performance data solutions on our Databricks platform. You will work alongside a small team of engineers through code reviews, design discussions, and delivery, while remaining deeply involved in the coding and implementation yourself. Your work will balance performance, cost, maintainability, scalability, and observability. 

Responsibilities:  

• Design, build, and maintain scalable batch and streaming data pipelines that feed our data warehouse and data lake 

• Understand the advantages and disadvantages of existing and proposed design solutions 

• Provide day-to-day technical leadership to a team of data engineers, including story definition, task planning, code review, and delivery oversight 

• Implement and follow data modeling, integration, and lifecycle standards established by the team, and contribute to refining them 

• Own the implementation and ongoing operation of our Databricks Cloud Data Warehouse, optimizing for performance, cost, scalability, and maintainability 

• Build data quality checks, lineage tracking, and metadata practices into pipelines from the start 

• Implement data governance controls (access, retention, accuracy, and integrity) in partnership with the governance and security teams 

• Apply security and privacy requirements, such as HIPAA and SOX, in pipeline and platform design as appropriate 

• Partner with data analysts and business stakeholders to understand data needs and explain technical tradeoffs clearly 

• Monitor, troubleshoot, and optimize data workflows, and lead root-cause analysis on production issues 

• Mentor and coach data engineers on engineering best practices, testing, CI/CD, and emerging tools 

• Additional responsibilities as assigned to help drive our mission of improving the lives of everyone living with cancer. 

Required Qualifications:

• Highschool diploma or GED 

• 7+ years of hands-on experience in data engineering or the Big Data domain.

• 2+ years leading or mentoring engineers in a technical lead or senior engineer role.

• Strong hands-on experience with modern Big Data technologies and cloud data warehouses (Databricks preferred, Snowflake, or Fabric is acceptable).

• Solid experience building scalable data solutions on a leading cloud platform (Azure preferred) 

• Proficiency in SQL and Python (or another OO Language).

Preferred 

• Experience in orchestration and transformation tools (e.g., Airflow, Azure Data Factory) 

• Working knowledge of data modeling methodologies (Dimensional, 3NF, Data Vault) and experience applying them in warehouse and data lake implementations.

• Experience implementing data governance, security, and compliance requirements in data pipelines.

Essential Competencies:  

• Strong communication skills, with the ability to explain technical challenges and solutions clearly to varied stakeholders 

• Proactive, productive, and analytical problem solver with a track record of troubleshooting and optimizing complex data workflows 

• Ability to break down projects into discrete tasks/components and create user stories for them 

• Attendance is an essential job function