Staff Data Engineer

As a Staff Data Engineer at Inari, your main duties include building integrated data products and pipelines from varied data sources to support multiple functions across the organization. You'll work closely with other engineers to facilitate data movement to diverse applications, thus providing insights into critical decision points in our product development pipeline, which is vital for our SEEDesign platform.

To qualify for the Staff Data Engineer role at Inari, candidates typically need a BS/MS in fields like Computer Science, Biotechnology, or Bioinformatics. Additionally, a minimum of 7 years of software/data engineering experience is required, especially in building data pipelines and delivering curated data products to support high-throughput data analysis for scientific applications.

Candidates for the Staff Data Engineer position at Inari should have expertise in Python and SQL along with familiarity with technologies such as Apache Airflow, Databricks, and Apache Spark. Knowledge of CI/CD practices, containerization technology, and data modeling will also be valuable assets for this role.

Working as a Staff Data Engineer at Inari promises a stimulating and fast-paced environment. You'll be engaged in cross-functional teams, collaborating with diverse professionals from various fields while contributing to innovative solutions aimed at sustainable agriculture. If you enjoy learning new technologies and facing fresh challenges, this role will be a perfect fit.

Inari stands out as an employer by fostering a diverse and inclusive environment where innovation and collaboration thrive. The company emphasizes the integration of experienced professionals and fresh talent from different disciplines, creating a rich tapestry of ideas and approaches to tackle critical challenges in agriculture. If you are passionate about making a positive impact, Inari is the place for you.

In your response, detail specific projects where you've designed and implemented data pipelines. Highlight the technologies used, challenges faced, and how you ensured data quality and integrity throughout the pipeline.

Articulate your process in defining data models, considering the needs of various stakeholders. Discuss how you balance performance, scalability, and complexity while ensuring the model supports business objectives.

Provide concrete examples of how you've utilized these technologies in previous roles. Explain your understanding of their strengths, limitations, and how you've leveraged them to solve specific problems.

Share a specific scenario that demonstrates your ability to communicate effectively with diverse stakeholders, such as scientists or product managers. Focus on how you ensured alignment and drove the project forward.

Discuss your strategies for continuous learning, such as attending workshops, webinars, or online courses. Highlight any recent breakthroughs or advancements that excite you and how they could be applied in your work.

Outline your approach to ensuring data quality and adhering to governance policies. Provide examples of how you've established or contributed to data governance frameworks in previous positions.

Describe a challenge you faced, the steps you took to troubleshoot the issue, what solution you implemented, and how it positively impacted the team or project.

Explain your commitment to automated testing in data engineering. Illustrate how you have implemented testing practices to ensure the reliability and accuracy of your data products.

Discuss your approach to task management and prioritization, mentioning specific techniques or tools you employ to balance competing demands and meet deadlines.

Reflect on Inari's mission, values, and innovative approach to agriculture. Convey your enthusiasm for contributing to a sustainability-focused organization and how your skills align with their goals.