Edge Platform Engineer

Key Responsibilities:

• Arsenal IT system architecture design by researching emerging technologies and providing strategic recommendations.
• Craft optimal data pipeline architectures capable of handling massive volumes while maintaining robust governance standards.
• Collaborate with Product and Business teams to re-engineer platforms and resolve complex technical challenges.
• Develop intelligent device control platform features deployed on Kubernetes environments, ensuring scalability and reliability.
• Establish diverse data connectivity capabilities across heterogeneous systems.
• Create cloud-native microservices libraries designed for seamless workflow pipeline integration.
• Architect solutions enabling non-stop service upgrades with zero-downtime operations.
• Implement advanced message exchange protocols leveraging new technologies.
• Deploy Big Data analytic platforms on high-availability NoSQL databases (Cassandra, HDFS, S3/MinIO, MariaDB, MongoDB) within K8s clusters.
• Scaffold and scale small data lakes into enterprise-level company-wide repositories.
• Construct scalable image/video lakehouses to manage semi-unstructured assets effectively.

Qualifications:

• Bachelor's degree in Computer Science, Electrical/Mechanical Engineering, or related fields (e.g., Data Engineering, Applied Mathematics).

Required Experience:

• Proficiency with container and cloud-native ecosystems including Kubernetes/Docker, Istio, ArgoCD, MongoDB, Redis.
• Solid background in microservices implementation, conductor workflows, Kafka queues on K8S.
• Hands-on experience connecting tools to IT systems such as IoT devices, Image/Voice platforms, SECS/GEM standards, PLC/DCS controls, and sensors.
• Versatility across big data ecosystems (Hadoop, Spark) and SQL NoSQL databases (MariaDB, MongoDB, MinIO).
• Expertise in orchestrating diverse data sources for parallel processing, metadata management, quality assurance, governance, security, and evaluating new technologies.
• Familiarity with object stores optimized for image and semi/unstructured data handling.
• Credentials in developing big data solutions and building pipelines for both batch and streaming applications.
• Experience utilizing monitoring tools like Nagios, ELK Stack, Splunk, and Grafana for analysis.
• Demonstrated ability to design independent high-level architectures without supervision.
• Mastery of cloud-native deployment practices focused on containers and orchestration platforms.