Senior Data Engineer

As a Senior Data Engineer at Dune, you will be responsible for building and maintaining data pipelines that power essential datasets for our platform. This includes assuming ownership of data transformation processes, orchestrating resilient pipelines, and supporting analysts in creating new datasets that meet the diverse needs of our community. Additionally, you will need to analyze and debug any pipeline issues that arise to ensure seamless data flow.

To qualify for the Senior Data Engineer position at Dune, candidates should have proven experience in building robust data pipelines and using orchestration tools, along with expertise in data warehousing technologies like Trino, Snowflake, or Clickhouse. Knowledge of public cloud deployment and infrastructure, strong computer science fundamentals, and collaborative skills in a remote environment are also essential. Familiarity with programming languages such as Python and SQL is highly preferred.

Senior Data Engineers at Dune typically work with a variety of tools and technologies that include data orchestration platforms like DBT and Prefect, as well as data warehouses such as Trino, Snowflake, or Clickhouse. Understanding of cloud platforms like Kubernetes is also crucial. By leveraging these tools, you will be able to build high-quality data pipelines and streamline the data transformation process for our users.

Senior Data Engineers at Dune enjoy numerous perks, including competitive salaries, generous equity packages, and flexible remote work arrangements. Employees also benefit from a strong work-life balance with ample PTO, private medical coverage, and parental leave policies. The company promotes a collaborative environment with opportunities for quarterly offsites, and you also receive a yearly allowance for your home office setup or local co-working spaces.

At Dune, supporting the professional growth of our Senior Data Engineers is a priority. The company offers exposure to cutting-edge technologies and methodologies in the blockchain space, encouraging team members to acquire new skills and contribute to impactful projects. Continuous learning is fostered through collaborative efforts, innovative solutions, and open-source contributions, allowing engineers to grow within a diverse and inclusive work culture.

When answering this question, focus on specific tools you've used, such as DBT or Prefect. Share any relevant projects where you implemented these tools, detailing the challenges faced and how you solved them. Highlight your ability to manage data flows efficiently and the improvements in data processing you achieved.

In responding to this question, explain your systematic approach to debugging. Discuss techniques like analyzing logs, validating data at various points in the pipeline, and using tools for monitoring performance. Share a specific example of a past debugging experience that showcases your problem-solving skills.

To showcase your experience, describe specific projects or tasks where you've worked with cloud infrastructures, particularly Kubernetes. Mention how you deployed applications, managed containerization, and ensured scalability. Highlight any challenges you overcame and how it benefited the organization.

Demonstrate your expertise by discussing your experience with SQL, mentioning specific queries, optimizations, or database management tasks. Also, include information about your experience with data warehousing systems like Snowflake or Clickhouse and how you've leveraged them for data analytics.

Discuss your time management skills and specific tools or methodologies you utilize to prioritize work remotely. Mention any personal techniques for maintaining productivity, such as setting daily goals or utilizing project management software to track progress on both individual and team tasks.

Provide a detailed overview of a data pipeline project you've successfully executed. Discuss the goals, tools used, challenges encountered, and the outcome. Highlight how your role directly contributed to its success and any positive impacts on users or stakeholders.

Explain your approach to ensuring data quality, which can involve validating input data, implementing data transformation checks, and conducting rigorous testing. Share any methodologies such as data profiling or version control you utilize to maintain data integrity throughout the pipeline process.

Discuss how you view collaboration as essential to successful data engineering. Provide examples of how you work with analysts and other engineers to gather requirements, troubleshoot issues, and optimize processes. Highlight any tools you use for communication and collaboration in a remote setting.

Provide insight into how you stay current with industry trends, such as attending conferences, participating in online courses, or engaging with data engineering communities. Mention specific resources like blogs, webinars, or podcasts that you find valuable for continuous learning.

Share your passion for the blockchain technology space, emphasizing its potential for innovation and transparency. Discuss any personal projects involving blockchain data or how you see yourself contributing to the mission of increasing accessibility and understanding within this domain.