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Collab, Inc. Remote.coabout 1 month ago
Apply Nowabout 1 month ago
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Location: US Locations; 100% Remote
Job Overview/Summary:
Trendpop is looking for a Senior Data Infrastructure Engineer to help us reverse engineer the algorithms that power virality on social media. Trendpop Core, our large-scale data infrastructure platform, ingests millions of social media posts and processes multiple terabytes per day to surface valuable insights for our customers. This person will work closely with our CTO to build the next phase of Trendpop Core infrastructure to support additional data sources, scale to the next order of magnitude, and glean smarter insights using cutting edge machine learning techniques. This person should be excited to work in a small but effective engineering team at a fast-paced startup. They will be given broad autonomy to tackle the toughest infrastructure problems we face every day!
Duties & Essential Functions:
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- Work with our CTO to design and implement the next generation of the Trendpop data infrastructure platform.
- Collaborate with internal teammates and external customers to prioritize / adapt the backend infrastructure over time to keep up with the needs of a fast-scaling software business.
- Partner with head of product to support the data infrastructure needs while assisting with data-related technical issues.
- Build, design and implement required infrastructure for optimal extraction, transformation and loading of data from various data sources.
- Other duties as assigned.
Skills & Required Qualifications:
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- 5-7 years of industry experience with distributed systems, data infrastructure, and systems programming.
- Experience in solving complex scaling, latency, or performance problems in high-volume distributed systems.
- Proficiency in at least one of the systems languages (Java, C++, Go).
- Demonstrated experience of designing a complex data infrastructure system.
Nice To Have:
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- Hands-on experience with big data/streaming technologies (e.g., Hadoop/Spark/Kafka).
- Previous experience working in a startup engineering team / in a start up environment.
- Familiarity with implementing and maintaining machine learning pipelines.