Data Collection

As a Data Collection Engineer at Singular, your main responsibilities will include building scalable data pipelines to process billions of events daily, developing new customer-facing products, and implementing innovative solutions that enhance our analytics platform. You'll work closely with our R&D team to tackle complex engineering challenges and ensure our architecture is both cost-effective and efficient.

The ideal candidate for the Data Collection Engineer position at Singular should hold a degree in Computer Science or Engineering, along with at least three years of software engineering experience. Key qualifications include proficiency in Python, SQL, and Django, a solid understanding of web technologies such as HTTP and APIs, and experience working with cloud storage platforms like AWS or GCP.

At Singular, we are committed to fostering the professional growth of our Data Collection Engineers. In this role, you will have opportunities to develop your engineering skills, participate in major projects, and collaborate with a high-caliber R&D team. We encourage every engineer to gain a deep understanding of our industry and leverage that knowledge in their work.

Yes! The Data Collection Engineer position at Singular is fully remote, allowing you the flexibility to work from anywhere. We believe that a diverse workforce with various backgrounds and experiences enhances our team's creativity and performance.

A Data Collection Engineer at Singular will engage in developing next-generation products that focus on attribution and analytics. You’ll be responsible for building and optimizing data pipelines, tackling complex engineering problems, and contributing to innovative solutions that help clients maximize their marketing ROI.

Discuss specific projects where you designed and implemented data pipelines, detailing the technologies used (like AWS), the challenges faced, and how you ensured scalability and efficiency while handling large datasets.

Provide examples of projects where you utilized Python for data processing and SQL for database management, explaining the impact your work had on project outcomes and team efficiencies.

Share your approach to debugging and optimizing APIs, including any tools or techniques you commonly employ. Mention specific incidents where you resolved issues quickly to maintain system performance.

Discuss your familiarity with AWS or GCP services relevant to data collection and processing, including any projects where cloud infrastructure played a crucial role in achieving objectives.

Outline your knowledge of data privacy regulations like GDPR or CCPA, and how you ensure compliance during data collection and processing in your engineering projects.

Emphasize the need for understanding user requirements, focusing on how data-driven products enhance user experience, and providing examples of how you’ve contributed to customer-facing solutions.

Describe your time management techniques, such as using Agile methodologies or task prioritization frameworks, and give examples of how you navigated competing deadlines in previous roles.

Share specific challenges related to coding, scaling, or data handling in previous projects and explain the processes you used to address these issues effectively.

Discuss your strategies for staying updated, such as attending conferences, following industry blogs, or participating in online communities, and provide examples of how you've applied new knowledge in your work.

Reflect on your passion for data engineering, such as the excitement of solving complex problems, creating impactful solutions, and continuously learning in a fast-paced technology environment.