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Sr Big Data​/OpenShift API Developer

Job in Charlotte, Mecklenburg County, North Carolina, 28202, USA
Listing for: Conflux Systems
Full Time position
Listed on 2026-09-05
Job specializations:
  • Software Development
    DevOps, Cloud Engineer - Software, Backend Developer
Job Description & How to Apply Below
Position: Sr Big Data / OpenShift API Developer

Sr Big Data / Open Shift API Developer

Location:

Charlotte, NC (Hybrid – 3 days office in a week)

Key Responsibilities

Platform Management

  • Deploy, configure, maintain, and support containerized Apache Spark applications on Open Shift and Google Cloud.
  • Manage Spark workloads running on Kubernetes and Open Shift clusters.
  • Configure pods, deployments, services, routes, secrets, config maps, resource quotas, and name spaces.
  • Define resource requests and limits for Spark drivers, executors, and supporting services.
  • Support cluster capacity planning, scaling, patching, upgrades, and environment management.
  • Maintain Helm charts and deployment templates for repeatable application releases.

Data Pipeline Development

  • Design and implement large-scale batch and streaming data processing workflows using Apache Spark and Apache Airflow.
  • Develop robust, reusable, and production-ready PySpark, Scala, or Java applications.
  • Build Airflow DAGs for scheduling, orchestration, dependency management, retries, and alerting.
  • Implement data ingestion, transformation, validation, enrichment, and publishing processes.
  • Support both real-time and batch data processing use cases.
  • Apply data engineering best practices for reliability, scalability, data quality, and maintainability.

API and Microservices Development

  • Design, develop, test, and maintain RESTful APIs and microservices supporting data and analytics platforms.
  • Define API contracts, request/response schemas, authentication mechanisms, error handling, and service-level requirements.
  • Integrate APIs with Spark applications, data platforms, databases, messaging systems, and cloud services.
  • Develop automated unit, integration, and API tests.
  • Apply microservices architecture principles, including loose coupling, scalability, resiliency, and observability.

Performance Optimization

  • Tune Spark jobs for performance, scalability, and efficient resource utilization.
  • Optimize partitioning, joins, caching, serialization, shuffle operations, file formats, and executor configuration.
  • Use Open Shift and Kubernetes resource-management capabilities to improve application performance.
  • Configure horizontal and vertical scaling, autoscaling, and workload scheduling where appropriate.
  • Analyze Spark execution plans, application logs, cluster metrics, and resource-consumption patterns.
  • Identify and resolve bottlenecks across applications, infrastructure, networking, and storage layers.

Integration

  • Integrate Apache Spark with data sources and platforms such as:
    • Apache Kafka
    • Amazon S3
    • Google Cloud Storage
    • Azure Blob Storage
    • HDFS
    • Relational and No

      SQL databases
    • Data lakes and data warehouses
  • Develop reliable ingestion and publishing patterns for batch and streaming data.
  • Implement schema management, checkpointing, offset handling, retry logic, and failure recovery.
  • Support secure connectivity between applications, cloud platforms, messaging systems, and databases.

CI/CD Implementation

  • Build and maintain CI/CD pipelines for deploying Spark applications, APIs, and supporting services to Open Shift.
  • Use tools such as Git Hub Actions, Sonar Qube, Harness, Docker, Helm, and Git.
  • Automate build, code-quality analysis, security scanning, testing, packaging, and deployment processes.
  • Implement environment-specific configurations and promotion strategies across development, QA, staging, and production.
  • Manage container images, registries, versioning, release tagging, and rollback procedures.
  • Establish deployment standards and support automated release management.

Monitoring and Troubleshooting

  • Monitor Open Shift cluster health, Spark job performance, application availability, and resource utilization.
  • Use Open Shift monitoring capabilities and tools such as Prometheus, Grafana, and centralized logging platforms.
  • Develop dashboards, alerts, health checks, and operational metrics.
  • Troubleshoot complex issues involving Spark applications, APIs, containers, Kubernetes resources, networking, storage, and integrations.
  • Perform root-cause analysis and implement proactive remediation.
  • Participate in incident, problem, and change-management activities.
  • Provide production support and participate in on-call rotations when required.

Security and Compliance

  • Implement…
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