Job Specifications
DevSecOps Platform Engineer
Location: Iselin, NJ (3 days onsite)
Employment: Long-term contract through March 2027
Level: Senior / Experienced
Overview
Seeking an experienced DevSecOps Platform Engineer to design, secure, and operate large-scale infrastructure supporting big data, analytics, AI/ML, and critical enterprise platforms. This role blends deep platform engineering, strong security practices, and automation skills to maintain a resilient, compliant, and high-performance environment.
You will work across containerized platforms, big data ecosystems, and cloud-native technologies, ensuring reliability, enforcing security standards, and driving automation across the stack.
Key Responsibilities Platform Engineering
Build, manage, and secure scalable, highly available infrastructure (Object Storage, OpenShift, Spark, Iceberg, Yunikorn, Trino).
Detect and remediate configuration drift; enforce platform security policies.
Configure and monitor Big Data components using BI/observability tools.
Create automated regression/performance tests to maintain system stability.
Handle cluster scaling, patching, and version upgrades.
Run security assessments and apply operational guardrails.
Security & Access Control
Implement OAuth, TLS/SSL, RBAC/ABAC models.
Enforce data protection standards (encryption in transit/at rest).
Validate compliance with IAM and regulatory frameworks (GDPR, HIPAA).
Harden Kubernetes and containerized workloads.
Monitoring & Observability
Monitor performance and system health across compute, storage, and data pipelines.
Implement observability using Prometheus, Grafana, and enterprise tools.
Work with operations teams on resiliency, HA, and disaster recovery.
Automation, CI/CD & DevSecOps
Build IaC automation with Helm, Terraform, Python, and shell scripts.
Enable repeatable, secure provisioning for platform and application services.
Integrate infrastructure changes into CI/CD processes with policy and compliance controls.
Required Technical Skills Programming & Scripting
Python, Bash/Shell, SQL
Basic Java; Scala preferred for big data
Strong scripting for automation and tooling
OS, Containers & Infrastructure
Deep Linux expertise (systems, networking, tuning)
Kubernetes, OpenShift, Helm, Terraform
Experience operating workloads in large enterprise clusters
Big Data & Data Engineering
Experience with Spark, Hadoop, Hive, Trino, Iceberg, NexusOne
Nice to have: Airflow, NiFi
Kafka/Flink for batch & streaming pipelines
Object storage: S3, NetApp StorageGrid
Familiarity with Parquet/Avro, ORC, JSON, CSV
AI/ML
ML frameworks or LLM workflows
MLflow, Kubeflow, SageMaker
Understanding of feature engineering and model deployment pipelines
Security & Compliance
RBAC/ABAC
TLS/SSL, encryption, KMS
GDPR/HIPAA awareness and IAM governance
Architecture (Good to have)
Microservices, event-driven systems
Load balancing, caching, horizontal scaling
HA, failover, DR, and monitoring architectures
Qualifications
Extensive experience in DevSecOps, platform engineering, data infrastructure, or cloud-native roles
Proven ability to operate distributed systems in regulated enterprise environments
Strong cross-team communication and collaboration with security, data, and operations groups
Skilled at troubleshooting, optimizing, and securing complex systems across compute, storage, and data layers
Posted By: Jon Szynalski