Data Platform Engineer

To be considered for the Data Platform Engineer role at Motive, candidates should possess at least 6 years of hands-on software engineering experience. A strong foundation in backend programming, including skills in concurrency and multithreading, is required. Familiarity with technologies such as Apache Kafka, Apache Spark, and Kubernetes is important, as well as a solid understanding of data structures and algorithms. A degree in Computer Science or a related field is expected, with a Master’s preferred.

As a Data Platform Engineer at Motive, you’ll be responsible for the design and development of scalable systems that handle data ingestion, processing, and storage. Key responsibilities include improving the ETL framework, collaborating with teams to implement features, ensuring high availability and fault-tolerance, and actively participating in the entire software development life cycle from design to delivery.

The Data Platform Engineer plays a critical role in enabling data-driven product features by building scalable systems and services for data management. By designing robust systems for data access and processing, and collaborating with backend product teams, you help unlock insights and improve operational efficiency, ensuring that both internal and external customers benefit from a high-performing data platform.

Motive fosters a collaborative and inclusive culture where diverse perspectives are valued. Data Platform Engineers work closely with various teams to address complex challenges and drive innovation. There’s a strong emphasis on communication, teamwork, and a shared commitment to fast-paced development aimed at modernizing the physical economy.

Absolutely! The Data Platform Engineer position at Motive not only offers the chance to engage in impactful work but also provides ample room for professional growth. Motive encourages continuous learning and offers opportunities to experiment with cutting-edge technologies, making it an ideal environment for engineers looking to advance their careers.

When answering this question, be specific about the distributed systems you've worked with, the challenges faced, and how you addressed them. Discuss your role in designing or implementing these systems, focusing on scalability, fault-tolerance, and high performance. Highlight any technologies you used, such as Apache Kafka or Kubernetes, to illustrate your experience.

Detail techniques you’ve employed for optimizing data ingestion, such as batch processing, real-time streaming, or using tools like Apache Spark. Discuss how you measure performance and reliability, and any challenges you overcame while enhancing these pipelines to meet SLA requirements.

Discuss strategies like load balancing, failover mechanisms, and redundancy that you've implemented to maintain high availability. Provide examples demonstrating your proactive measures to avoid downtime and ensure seamless access to services.

Share a specific project where you designed or enhanced a service-oriented architecture. Explain the context, your role, and the impact it had on system efficiency and flexibility. Highlight your design choices and any principles you followed.

Discuss your systematic approach to troubleshooting, including tools and techniques you use to identify the root cause of issues. Provide examples of past incidents where your troubleshooting skills led to successful resolutions, and how you documented and communicated these learnings.

Emphasize the importance of teamwork in developing complex systems. Discuss instances where collaboration with cross-functional teams enhanced the quality of your work and mention how you communicate effectively to align goals and share progress.

Provide a brief explanation of multithreading and its significance in software engineering. Share specific examples of how you've utilized multithreading to improve application performance, addressing challenges like concurrency and resource management.

Describe approaches to testing, such as unit tests, integration tests, and performance benchmarks. Highlight how thorough testing contributes to system reliability and your commitment to quality assurance throughout the development process.

Talk about your commitment to continuous learning, including following industry publications, attending conferences, and participating in online courses. Explain how this knowledge informs your work and enhances your contributions as a Data Platform Engineer.

Share your motivation for applying to Motive, focusing on the company's mission to modernize the physical economy and its reputation as an innovative player in the industry. Match your personal values and professional goals with the role and company culture.