As a Sr. Data Engineer at Auger, you will be primarily responsible for designing and implementing data ingestion pipelines for various data sources, both batch and real-time. You will also develop monitoring frameworks to ensure data quality, as well as support data modeling and architecture to meet analytics requirements. In addition, you’ll work closely with the team to explore multi-modal data types and ensure the scalability of our data lake to accommodate significant growth.

To be considered for the Sr. Data Engineer position at Auger, you need a degree in Computer Science, Mathematics, Statistics, or a related data-intensive field, along with at least 7 years of development experience using SQL, Java, Scala, Spark, Python, or similar technologies. Familiarity with modern database technologies and experience in managing structured and unstructured data is also crucial for success in this role.

Candidates for the Sr. Data Engineer role at Auger should have experience with SQL, Java, Scala, Spark, Flink, Beam, and Python. Additionally, familiarity with modern database technologies, multi-cloud providers like AWS and Azure, and tools for developing data pipelines such as dbt and Dagster will enhance your ability to contribute effectively to our team.

The Sr. Data Engineer role at Auger is crucial for enhancing supply chain efficiency by developing analytical approaches that transform raw, complex data into actionable intelligence. This optimization enables organizations to make faster, data-driven decisions, ultimately improving supply chain operations and promoting sustainability while addressing the genuine human issues that arise when supply chains fail.

The work culture at Auger is energetic and collaborative, designed for those who thrive in a startup environment. As a Sr. Data Engineer, you will work alongside talented professionals who are passionate about tackling complex challenges with resilience and good humor. Our team values curiosity, agile methodologies, and a supportive atmosphere where innovative ideas can flourish.

When answering this question, highlight specific projects where you successfully developed data ingestion pipelines. Discuss the technologies you used, the types of data sources involved, and how your work improved data accessibility or quality. Focus on the scalability of the pipelines and how they supported more extensive data processing tasks.

In your response, discuss the importance of monitoring frameworks and how you implement checks at various stages of data processing. Provide examples of specific tools or methods you've employed to maintain data integrity. Sharing success stories will demonstrate your practical knowledge and commitment to data quality.

When addressing this question, outline your experience with multi-cloud providers such as AWS and Azure. Discuss specific projects where you leveraged multi-cloud architectures, the challenges you faced, and how you overcame them. Emphasize your adaptability and ability to optimize performance across different cloud environments.

Begin by mentioning a particular project involving large datasets. Detail the challenges you faced, such as data storage, processing speed, or integration issues. Discuss the strategies you implemented to handle these challenges effectively and the positive outcomes that resulted from your solutions.

Talk about your method for determining the needs of the business and the types of data involved. Describe the steps you take to create flexible, scalable architectures that can adapt to future growth. Highlight any frameworks or best practices you follow, and provide examples of successful implementations in your prior work.

Share specifics about your experience with each language, including types of projects, tools, and techniques you've utilized. Focus on how you apply these languages to solve data-related problems and the impact your coding skills have had on your past teams or projects.

Mention the resources you use, such as blogs, online courses, or industry meetups, to stay informed about developments in data engineering. Highlight your commitment to lifelong learning and how you apply new concepts and tools to improve your work, making you a more effective Sr. Data Engineer.

Choose a specific project where your work directly influenced important decisions within your organization. Discuss the data you provided, how it was analyzed, and the results of the decision made. This will demonstrate not just your technical skills, but also your impact on business processes.

Address this by explaining your approach to working collaboratively with stakeholders to clarify their goals. Discuss how you ask probing questions to reveal underlying needs and ensure project success. Highlight any specific experiences where you successfully navigated ambiguity to deliver a strong solution.

In your answer, discuss how data engineering can drive efficiency and reduce waste within supply chains. Emphasize the importance of accurate data for informed decision-making and how this can lead to sustainability efforts such as optimizing routes, reducing energy consumption, or minimizing overproduction. Connect this to your vision as a Sr. Data Engineer at Auger.