Software Engineer - Data Infrastructure

As a Software Engineer - Data Infrastructure at Figma, you'll design and implement large-scale distributed data systems that power analytics, AI/ML, and business intelligence. Your responsibilities include developing efficient batch and streaming solutions, managing data ingestion, and ensuring data reliability and quality across various platforms like Snowflake and the ML Datalake. Collaboration with cross-functional teams to understand data needs and drive technical decisions will be a significant part of your role.

To be considered for the Software Engineer - Data Infrastructure role at Figma, applicants should have at least 6 years of experience in designing distributed data infrastructure at scale. A strong background in batch and streaming data processing technologies such as Spark, Flink, and Kafka is essential. Additionally, candidates should exhibit strong problem-solving skills, technical communication abilities, and the capacity to navigate ambiguity in a fast-paced environment.

In the Software Engineer - Data Infrastructure position at Figma, you will commonly encounter technologies such as Snowflake for data warehousing, Spark and Flink for batch and streaming processing, and Kafka for real-time data streaming. Familiarity with tools like Airflow/Dagster, Golang, Python, and SQL will also be highly beneficial in this role as they are integral to building scalable infrastructure for data operations.

The team environment for Software Engineers - Data Infrastructure at Figma is collaborative and innovative. The small yet dynamic team takes on high-impact tasks while fostering a culture where engineers can mentor one another and share knowledge. You will be part of a diverse working group, engaging with AI researchers, data scientists, and product engineers to ensure a holistic approach to data solutions.

At Figma, a Software Engineer - Data Infrastructure can expect to work on a variety of exciting projects, such as revamping orchestration architectures, developing interconnects for streaming between core systems, and enhancing data quality and reliability. These projects aim to improve data processing efficiency and support AI-driven initiatives that will have a significant impact on how products are designed and brought to market.

In your response, focus on specific projects you've led or contributed to, emphasizing the architecture you designed, the technologies used, and the outcomes achieved. Demonstrating your ability to tackle scalability and reliability concerns will reflect your suitability for the Software Engineer - Data Infrastructure role.

Detail the specific technologies like Spark, Flink, Kafka, or Airflow/Dagster that you have worked with. Discuss how you utilized these tools to solve problems or enhance data processes in previous roles, showcasing your technical proficiency relevant to Figma's needs.

Discuss the practices or tools you've implemented to monitor data quality and how you've responded to data consistency issues in past projects. Highlight any specific frameworks or methodologies that align closely with the data quality goals at Figma.

Share examples from past experiences where you've effectively communicated complex technical concepts to non-technical stakeholders. Emphasize your ability to listen, understand their needs, and translate them into actionable data solutions.

Explain a specific situation where clear guidelines were lacking, detailing how you assessed the situation, engaged the team when necessary, and drove the project to completion by being proactive and flexible.

Describe your mentoring style and techniques. Illustrate how you transfer knowledge and support the growth of junior engineers through coding reviews, paired programming, or organizing tech talks, ensuring to emphasize a culture of learning.

Choose a relevant and specific challenge you faced and explain the problem-solving process you used, including the analysis, tools, and strategies you employed to resolve the issue effectively.

Discuss the resources you use, such as online courses, blogs, conferences, or communities that focus on data engineering. Highlight your commitment to continuous learning and adaptation, which resonates with Figma's value of growing as you go.

Share your understanding of data governance principles and the importance of access control. Discuss specific strategies or experiences you have related to maintaining data integrity and compliance in your past roles.

Reflect on your passion for data engineering, how it aligns with Figma's mission, and how you believe your skills can contribute significantly to the team's goals. Make it personal by mentioning what excites you about Figma's culture and technology.