Senior Software Engineer, Data Ingestion

As a Senior Software Engineer at Astronomer, your primary responsibilities will include designing and implementing the OpenLineage data collection and ingestion efforts for our data observability product, Astro Observe. You'll collaborate with cross-functional teams to understand user requirements and develop features that enhance visibility into data pipelines. Additionally, you will contribute to the OpenLineage and Airflow Open Source community, focusing on the usability, reliability, and scalability of the overall platform.

To be considered for the Senior Software Engineer role at Astronomer, candidates are expected to have over 5 years of engineering experience, proficiency in Python, and strong skills in software development best practices like code reviews and CI/CD. Additionally, familiarity with tools like Apache Airflow, OpenLineage, and data observability products can set you apart. Effective communication skills are essential for collaboration within our diverse team.

At Astronomer, the work culture is inclusive and emphasizes innovation and collaboration. As a Senior Software Engineer, you can expect to work in a remote-first environment where diverse experiences and unconventional pathways are celebrated. This culture encourages continuous learning and provides plenty of opportunities to contribute to exciting projects and connect with talented colleagues from around the world.

Astronomer is keen on investing in the career growth of its Senior Software Engineers. You will have access to various professional development opportunities to broaden your technical skills, especially within the data ingestion and observability domains. Moreover, you'll be encouraged to contribute to the Open Source community, gaining exposure, and building a network in the industry which can significantly aid your professional journey.

The estimated salary range for the Senior Software Engineer position at Astronomer is between CA$190,000 - CA$220,000, depending on your skills, experience, and level within the company. This compensation offer also includes equity components and a comprehensive benefits package to ensure a balanced and rewarding work experience.

When answering this question, focus on specific projects where you utilized Python, emphasizing any libraries or frameworks that you found effective. Highlight how your Python skills contributed to efficient coding practices, automation, or data manipulation tasks, particularly in observability or ingestion contexts.

Discuss specific debugging techniques you employ, such as using logging tools, breakpoints, or unit tests. It’s also useful to provide examples of past debugging challenges you faced and how you resolved them, showing your problem-solving skills and thorough approach.

Outline your step-by-step approach starting from understanding the data requirements, defining scalability needs, and selecting appropriate tools. Mention any design principles or patterns you follow that enhance performance and reliability in data ingestion pipelines.

Respond with a detailed description of a project where you worked with OpenLineage, specifically explaining your role, the challenges faced, solutions implemented, and the overall impact on visibility or observability outcomes.

Your response should illustrate how CI/CD pipelines have streamlined your development process, reduced deployment times, and increased the reliability of deliveries. Provide an example of a CI/CD setup you implemented or managed.

Talk about the coding standards and best practices you follow, such as code reviews, static analysis tools, or unit tests. Mention how these practices contribute to maintainability and collaboration within your team.

Share a specific instance that illustrates your ability to communicate and collaborate with members from different backgrounds, emphasizing how you navigated any challenges and achieved shared goals.

Detail your experience with Apache Airflow, including how you’ve used it to manage data pipelines. Mention any specific tasks you completed using Airflow, showcasing your understanding of its key features and functionalities.

Explain your strategies for keeping up-to-date, such as attending workshops, following industry leaders on social media, engaging in coding community forums, or participating in open-source projects that enhance your skills.

Provide insights into what data observability means and its critical role in ensuring data integrity, reliability, and performance within data pipelines. Illustrate your awareness of the impact that strong observability practices have on decision-making processes.