A company is looking for a Senior Engineer, Data Platforms to enhance their data processing infrastructure and analytics capabilities.
Key ResponsibilitiesDesign and implement scalable big data systems processing large volumes of healthcare dataDevelop and architect cloud-event microservices and Spark applications for real-time and batch processingCollaborate with cross-functional teams to deliver quality solutions and mentor junior engineersRequired Qualifications5+ years of experience in distributed systems and cloud-native technologiesProficiency with Java, Spark, and KubernetesExtensive experience with cloud platforms (AWS, GCP, or Azure)Familiarity with Data Lake and Lakehouse architectureExperience mentoring junior engineers and influencing architectural decisions
Senior Data Engineer
A company is looking for a Senior Data Engineer to join their Data Engineering Team. ...
Senior Platform Engineer (Enterprise Platforms Technology)
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A large equipment manufacturing company is seeking a Senior Data Engineer to develop and execute the data analytics strategy encompassing the acquisition, processing and ML of engineering or service data. Assist with data quality and security, ensuring proper data governance within the enterprise da...
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Senior Staff Engineer- Data Center Hardware
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GEICO is seeking an experienced Senior Engineer with a passion for building high-performance, low maintenance, zero-downtime platforms, and applications. Our Senior Engineer is a key member of the engineering staff working across the organization to provide a friction-less experience to our customer...
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As a senior member of the team, you bring deep expertise in data engineering and will work closely with other infrastructure and network engineers, data scientists, and system engineers on the following key tasks:. Ensure data integrity by performing employing data engineering best practices. Mainta...
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The ideal candidate has broad and deep technical knowledge and all points in between, and a proven background in Java, Linux, Microservices, Containers (Kubernetes), database modeling, open-table format, performance tuning, query optimization, data sharding, partitioning, building, configuring, and ...