Skip to content
Principal Data Engineer
| Company | Saviynt |
|---|
| Location | California, USA |
|---|
| Salary | $215000 – $280000 |
|---|
| Type | Full-Time |
|---|
| Degrees | |
|---|
| Experience Level | Senior, Expert or higher |
|---|
Requirements
- 8+ years of experience in Data Engineering, DevOps, or Software Engineering, with a focus on ElasticSearch administration and optimization.
- Proven experience upgrading ElasticSearch (6.x to 7.x, 7.x to 8.x) in a production environment.
- Strong expertise in ElasticSearch performance tuning, cluster scaling, and optimization techniques.
- Experience designing and implementing multi-tenant solutions in ElasticSearch.
- Hands-on experience with indexing strategies, data partitioning, and sharding techniques.
- Solid understanding of Elasticsearch security best practices, including TLS encryption, role-based access control (RBAC), and secure data storage.
- Proficiency in SQL, NoSQL databases, and data storage technologies (e.g., MySQL, Redis, S3).
- Experience integrating ElasticSearch with Java/SpringBoot applications and working with RESTful APIs.
- Strong knowledge of cloud platforms (AWS, Azure) and experience deploying ElasticSearch in containerized environments (Docker, Kubernetes).
- Experience with infrastructure automation tools (Terraform, Ansible, Helm, or CloudFormation) for managing ElasticSearch clusters.
- Strong problem-solving and analytical skills with the ability to troubleshoot complex distributed systems.
- Excellent communication and collaboration skills to work cross-functionally with engineers, architects, and business stakeholders.
Responsibilities
- Lead and execute ElasticSearch upgrades from version 6.x to 7.x and from version 7.x to 8.x, ensuring minimal downtime and smooth migrations.
- Design and implement best practices for scalability, performance tuning, and security of ElasticSearch clusters.
- Optimize search indexing and query performance for large-scale datasets, improving search relevance and efficiency.
- Develop and maintain monitoring and alerting mechanisms for ElasticSearch clusters, ensuring high availability and resilience.
- Collaborate with cross-functional teams (Engineering, DevOps, Security) to integrate ElasticSearch with existing applications and infrastructure.
- Evaluate and implement multi-tenant architecture within ElasticSearch to support large-scale deployments across multiple customers.
- Define and enforce best practices for data modeling, indexing strategies, and cluster sharding to ensure optimal system performance.
- Troubleshoot and resolve ElasticSearch issues related to query performance, data consistency, and infrastructure scaling.
- Maintain and enhance security configurations, including encryption, access control, and compliance with industry standards.
- Automate operational tasks using scripting and infrastructure-as-code (IaC) tools for ElasticSearch management.
- Mentor and guide engineers on ElasticSearch administration, optimization, and best practices.
Preferred Qualifications
No preferred qualifications provided.
