Distributed Systems Engineer
دوام كامل
في BigGeo
في
Canada
نُشرت يوم February 8, 2025
تفاصيل الوظيفة
Employers often ask why you'd be a good fit to work for them. At BigGeo, we prefer to start by showing why we’re a good fit for you. Why You’d Want to Work at BigGeo :
- Be part of a pioneering team driving the future of geospatial intelligence.
- Work in an innovative, data-driven environment that values creativity and rapid problem-solving.
- Experience firsthand how your contributions shape cutting-edge technologies and serve critical industries globally.
- Embrace a modern “self-care” work schedule that emphasizes balance and well-being.
- Shape products that solve major global challenges, from urban planning to environmental conservation.
- Design and implement distributed systems that process and analyze large-scale geospatial datasets.
- Solve challenges related to fault tolerance, consistency, availability, and performance in distributed systems.
- Collaborate with product managers, engineers, and other stakeholders to deliver high-quality solutions.
- Analyze and improve system scalability to accommodate rapidly growing datasets and users.
- Ensure operational readiness, including monitoring, documentation, and incident response capabilities.
- Stay current on emerging technologies and trends in distributed systems and apply them to BigGeo’s platform.
- 5+ years of experience designing, building, and maintaining distributed systems in production environments.
- Strong computer science fundamentals, including expertise in algorithms, data structures, and distributed systems principles.
- Proficiency in systems programming languages such as C++, Java, or similar.
- Proficiency in Java with strong knowledge of multi-threading, concurrency, and memory management.
- Experience with data processing frameworks such as Apache Iceberg, Hadoop, Spark, or equivalent technologies.
- Solid understanding of multi-threading, concurrency, memory management, and other low-level programming concepts.
- Experience with cloud infrastructure, preferably AWS, Azure, or Google Cloud.
- Experience in Ray, Dask, Presto/Trino, Apache Spark, etc.
- Ability to diagnose and resolve complex issues in distributed environments.
- Familiarity with geospatial data formats, tools, and frameworks.
- Experience building large-scale, data-intensive systems or pipelines.
- Experience leading technical initiatives or mentoring team members.
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