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Engineering Jobs

Core Platform Engineer

PeopleNTech LLC

  • Alexandria, VA
  • 10 days ago
  • $65–$67 Per Hour

Highlights

Responsibilities: Support a highly available and scalable infrastructure containing Object storage, Openshift, Spark, Iceberg, Yunikorn, Trino. Security & Access Control Access Models : RBAC (Role-Based Access Control), ABAC (Attribute-Based Access Control).

Numbers & Facts

LocationAlexandria, VA
Salary$65–$67 Per Hour

Description

Indent :SF_OP_189416-1-1
Role : Core Platform Engineer
Location : Charlotte-Concord-Gastonia, NC-SC (Hybrid)
Rate: $65/hr - $67/hr

Core Platform Engineer
  • Primary Role: Build and maintain secure, scalable infrastructure and services.
  • Responsibilities:
    • Support a highly available and scalable infrastructure containing Object storage, Openshift, Spark, Iceberg, Yunikorn, Trino
    • Monitor for configuration drift and enforce infrastructure policies.
    • Configure and monitor Big Data ecosystem components with various BI tools, observability tools etc
    • Build automated regression and performance test suite to ensure health checks of all components of the platform
  • Tasks:
    • Monitor system health and enforce runtime policies.
    • Implement and manage security protocols, including Oauth authentication, TLS encryption, and role-based access control (RBAC).
    • Conduct regular maintenance, including cluster scaling, perform regular security audits.
Programming & Scripting
  • Languages: Python, Bash, Shell, SQL, Java (basic), Scala (for big data, good to have)
  • Automation & Scripting: Python scripting for automation, Linux shell scripting
Operating Systems & Containers
  • System programing, performance tuning, networking
  • OCP, Kubernetes (K8s), Helm, Terraform, container orchestration and deployment
Big Data & Data Engineering
  • Frameworks: NexusOne, Apache Spark, Hadoop, Hive, Trino, Iceberg
  • ETL Tools: Apache Airflow, NiFi (good to have)
  • Data Pipelines: Batch and streaming (Kafka, Flink)
  • Object Storage: S3, NetApp StorageGrid
  • Data Formats: Parquet/Avro, ORC, JSON, CSV
AI/ML & MTC (Model Training & Consumption) (Nice to have)
  • Frameworks or LLM modeling
  • Model Ops: MLflow, Kubeflow, SageMaker
  • Data Science: Feature engineering, model deployment, inference pipelines
Security & Access Control
  • Access Models: RBAC (Role-Based Access Control), ABAC (Attribute-Based Access Control)
  • Data Protection: Encryption at rest and in transit, TLS/SSL, KMS (Key Management Services)
  • Compliance: GDPR, HIPAA (if applicable), IAM policies
System Design & Architecture (good to have, at least at a conceptual level)
  • Design Principles: Microservices, Event-driven architecture, Serverless
  • Scalability: Load balancing, caching (Redis, Memcached), horizontal scaling
  • High Availability: Failover strategies, disaster recovery, monitoring (Prometheus, Grafana)

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