About Business Unit:
A consolidated team of database technology professionals, we deliver expert insights across all major database engines and Big Data solutions to support Epsilon products and platforms. The team has a one-of-a-kind alignment that combines a horizontal organizational structure with vertically aligned sub-groups dedicated to our clients. By adhering to consistent standards and methodologies, the team ensures operational excellence and has close ties with product teams at Oracle, IBM, Cloudera, Amazon and Microsoft.
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Design, implement, and manage CI/CD pipelines for microservices and data workloads
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Build and maintain cloud-native infrastructure (AWS/Azure/GCP) using Infrastructure as Code.
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Support deployment and orchestration of microservices-based applications (Docker, Kubernetes)
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Manage and optimize Databricks environments for data engineering and analytics workloads
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Automate operational workflows, monitoring, and alerting for high availability systems
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Collaborate with development, data engineering, and platform teams to ensure seamless delivery
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Ensure security, compliance, and cost optimization across cloud resources
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Troubleshoot deployment, performance, and infrastructure issues
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5+ years of experience in DevOps & Microservices
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Proficiency in backup and recovery methodologies and techniques
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Ability to diagnose problems and resolve issues across various tiers (application, database , network and appliance)
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Adherence to SDLC, Change Management, troubleshooting and development methodologies
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Strong Unix/Linux and shell scripting
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Ability to perform work with minimal supervisory direction
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Excellent written and verbal communication skills
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Strong hands-on expertise with:
- CI/CD tools: Azure DevOps, Jenkins, GitHub Actions
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Containerization: Docker
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Orchestration: Kubernetes (EKS/AKS/GKE)
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Experience with microservices architecture and distributed systems
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Solid experience with Databricks (cluster management, job orchestration, integrations)
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Strong scripting skills (Python / Bash / PowerShell)
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Experience with Infrastructure as Code (Terraform / ARM / CloudFormation)
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Knowledge of monitoring tools (Prometheus, Grafana, CloudWatch, Azure Monitor)
Preferred Skills
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Experience with data engineering pipelines (Spark, Delta Lake)
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Exposure to streaming architectures (Kafka, Event Hubs)
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Understanding of data lake / lakehouse architectures
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Experience with multi-region / high-availability setups
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Cloud certifications (AWS / Azure DevOps / Databricks)
Education/Certification
B.S. in Computer Science or related field or equivalent work experience required. AWS certification is a plus.
