Sr. Data Engineer
OneOncology
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 strong Sr. Data Engineer for a full-time role based in Austin, TX, Nashville, TN, or remote. Our development team is a small group and the person filling this role will be an integral part of it. All team members are individually motivated, yet collaborative. We maintain a high degree of accountability, are extremely productive and believe in enjoying our time at work.The ideal candidate is a hands-on platform builder with extensive experience in developing scalable software and data platforms. The Sr. Data Engineer engages directly with IT management, development teams, technical delivery teams, and vendors to ensure the successful design, development, and delivery of technology-based solutions. They thrive in an agile environment, demonstrate strong initiative, and communicate effectively across teams.
Responsibilities:
- Design & implement robust, componentized, and scalable data processes to that enhance and expand our business intelligence platform
- Rapidly gain proficiency with big data and cloud technologies, leveraging them to build, optimize, and analyze large-scale data solutions.
- Translate complex business requirements into clear technical deliverables, proactively identifying dependencies, risks and potential roadblocks.
- Deliver high-quality, maintainable code efficiently, following best practices for version control, testing and deployment.
- Collaborate with stakeholders to gather requirements, assess technical needs, and design solutions aligned with business objectives.
- Continuously identify & implement improvements to optimize data pipelines, system performance & overall process efficiency.
- Mentor and teach team members on modern data engineering concepts, industry standards, and internal best practices.
- Demonstrate adaptability in a dynamic environment, effectively prioritizing work as requirements and priorities evolve.
- Troubleshoot and resolve complex issues, maintaining system stability and minimizing disruptions to operations.
- Take ownership of code, architecture, and documentation, communicating implementation details clearly to technical and non-technical audiences.
- Document processes
- Stay current with emerging technologies and industry standards, applying best practices in healthcare data engineering & development.
- Additional responsibilities as assigned to help drive our mission of improving the lives of everyone living with cancer.
- 8+ years of hands-on experience with SQL development.
- 8+ years of experience working with relational and non-relational databases, with a strong foundation in data modeling, schema design, and query optimization.
- 5+ years of professional experience developing scalable solutions using Python or a similar object-oriented language.
- Proficient in Databricks, Spark, and Delta tables; experience with large-scale distributed data processing preferred.
- Solid understanding of Lakehouse and Medallion architectures.
- Experience designing Data Integration/ETL pipelines using Azure Data Factory or equivalent.
- Extensive experience deploying and managing solutions in cloud environments (preferably Microsoft Azure), including monitoring, cost optimization, and data security.
- Strong understanding of Object-Oriented Design (OOD) principles and software engineering best practices.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field; or equivalent work experience.
- Demonstrated ability to design and implement scalable, reliable data ecosystems.
- Demonstrated expertise in building and maintaining robust, automated data pipelines.
- Skilled in implementing instrumentation, logging, and alerting strategies to ensure data reliability and observability.
- Proactive and analytical problem-solving skills with the ability to troubleshoot and optimize complex data workflows.
- Attendance is an essential job function.
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