Software Engineer, Audience
Greater LA Area
1 day ago
Spatiotemporal data processing. We use a combination of industry-standard tools and custom libraries to efficiently represent, partition, and store geospatial information. Our biggest challenges happen where theoretical considerations meet real world data.
Big Data / MapReduce. For data processing and storage, we primarily use Hadoop, and invest our effort here in finding the right approaches to sorting, managing pipelines, serialization/deserialization, and the integration of batch and real-time processing.
Performance tuning, especially on the JVM. On the opposite side of our big data challenges are the code paths that are executed millions of times per second. Here we leverage a combination of flame graphs, wrk2 and other benchmarking tools, and YourKit / VisualVM profiling to maintain performance even as we grow in scope and scale.
Management of Java teams and large Java codebases. As Factual continues to grow, we're focusing on establishing the right processes around design and architecture, coding best practices, and effective methodologies as they relate to Java software development.