Key skills
KubernetesAWSAirflowSnowflakePythonSQLAutomated testingSoftware engineering best practicesSelf-managementClear communicationMachine LearningJiraScrumKanbanChange ManagementCommunication
About this role
Doximity is transforming the healthcare industry, aiming to help every physician be more productive and provide better care. The Senior Software Engineer on the Data Platform team will design and implement systems to enhance the data stack, working closely with data analysts and engineers to address their needs and challenges.
Responsibilities:
- You will work closely with data analysts, data engineers, and machine learning engineers, understanding their future needs and current challenges
- Your role will be pivotal in ensuring that the Doximity data stack evolves to meet these future requirements and alleviate existing obstacles
- Understand what our data product teams are trying to achieve
- Principally, to help you propose, architect, design, and implement solutions and best practices to maximize the time they can spend on their immediate goals, while minimizing the time they need to spend on unrelated or redundant technical hurdles
- You will play a key role designing and implementing systems, or refining existing ones, that form the foundations of our data platform
- Applying your expertise and delivering results will be instrumental in achieving this
- Working with colleagues on the data platform team and other infrastructure teams, you will help provide insights into the performance and stability of the foundational systems of the data platform through thoughtful monitoring and analysis
- Alongside the rest of the data platform team, you will form the last line of defense in resolving problems facing members of our product data teams
Requirements:
- Experienced data platform engineer with a track record of delivering high-quality solutions that empower data teams to achieve their goals
- Expertise in Kubernetes, AWS, Airflow, and Snowflake
- Fluent in Python and, ideally, comfortable with SQL for routine data analysis
- Strong commitment to high-quality code, automated testing, and software engineering best practices
- Ability and drive to self-manage, prioritize tasks, and deliver functional solutions
- Clear and timely communication, both written and verbal
- Recognize the value of using software-development lifecycle tools and processes such as Jira, scrum, Kanban, change management, changelogs, and well-documented code