
Data Architecture Specialist
1 semana atrás
This challenging role involves leading teams to optimize data product runtime architecture within a cloud-based environment. As an expert in distributed computing, you will drive strategic decision-making and technological advancements.
Key Responsibilities:- Refine Spark workloads to enhance performance and resource efficiency, including tuning parameters and re-engineering data processing pipelines.
- Implement monitoring solutions to detect and diagnose performance bottlenecks or failures in Spark applications.
- Collaborate with teams to design and build a framework that allows seamless scalability across distributed data environments.
- Document Spark optimization best practices and conduct training sessions to enhance team expertise.
- Lead AI-automation initiatives to improve workload scalability and efficiency.
- Deep understanding of concurrency, fault tolerance, and network latency principles.
- Comprehensive knowledge of Apache Spark architecture and execution models.
- Expertise in performance profiling and tuning Spark applications.
- Proficiency in writing efficient SQL queries and transformations using SparkSQL and DataFrames.
- Strong debugging skills for runtime issues and environment configurations.
- Experience with monitoring tools such as Spark's web UI, Ganglia, Grafana, or Prometheus.
- Understanding of AI and ML trends and their applications in distributed data processing.
- Excellent leadership, mentorship, and communication skills.
Join a collaborative and inclusive culture focused on innovation, learning, and development. This is an opportunity to bring out your best and be part of a purpose-driven organization.
Inclusion and Equal Opportunity:We value diversity and are committed to creating an inclusive environment. We are an equal opportunity employer and provide accommodations for applicants with disabilities.
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