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Sr Big Data/OpenShift API Developer
Job in
Charlotte, Mecklenburg County, North Carolina, 28202, USA
Listed on 2026-09-05
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
Sr Big Data / Open Shift API Developer
Location:
Charlotte, NC (Hybrid – 3 days office in a week)
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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