Overview
Remote
$40 - $60
Full Time
Skills
Conflict Resolution
Apache Velocity
Business Support Systems
Caching
Collaboration
Communication
API
Data Governance
Data Integrity
Data Migration
Data Retention
Continuous Delivery
Continuous Integration
Data Engineering
Data Flow
Design Architecture
Java
JavaScript
Knowledge Base
Licensing
Lifecycle Management
Documentation
Elasticsearch
Extract
Transform
Load
GitLab
Issue Resolution
Access Control
Agile
Analytical Skill
Analytics
Migration
Network
Apache Kafka
Dashboard
Linux
Log Management
Management
Microservices
Job Details
The OpenSearch Developer / Data Engineer will design, build, and maintain large-scale data ingestion, transformation, and indexing pipelines supporting T-Mobile s observability and analytics ecosystem. This role is responsible for migrating critical network telemetry and log data from Splunk to OpenSearch, implementing efficient ETL processes, and ensuring high-performing, scalable, and secure data workflows.
The engineer will collaborate closely with data scientists, architects, and application developers to optimize search performance, enforce data governance, and reduce operational cost while ensuring reliable and actionable insights from network data.
Key Responsibilities 1. Data Engineering & ETL Development
The engineer will collaborate closely with data scientists, architects, and application developers to optimize search performance, enforce data governance, and reduce operational cost while ensuring reliable and actionable insights from network data.
Key Responsibilities 1. Data Engineering & ETL Development
- Design and implement ETL (Extract, Transform, Load) processes to handle complex data ingestion workflows.
- Develop data pipelines to collect, normalize, and route high-volume log and telemetry data from multiple sources (network, OSS/BSS, application systems).
- Migrate existing data sets from Splunk to OpenSearch, ensuring data integrity, consistency, and traceability.
- Optimize ingestion and query performance through indexing, partitioning, and caching strategies.
2. OpenSearch Integration & Administration
- Configure, manage, and maintain OpenSearch clusters, ensuring scalability, fault tolerance, and performance optimization.
- Design and implement indexing strategies and mappings for high-volume network data.
- Implement fine-grained access control, data lifecycle management, and retention policies.
- Create dashboards and analytics visualizations for operational insights, where applicable.
3. Application & Microservices Development
- Develop Java-based backend services and utilities that support data ingestion, query processing, and API integrations.
- Write efficient scripts and automation utilities using Python, Perl, or JavaScript for ETL orchestration and validation.
- Develop and maintain Kafka producers/consumers for real-time event streaming and data flow into OpenSearch.
4. Quality, Testing & Deployment
- Write and execute unit, integration, and performance tests to validate data migration and ingestion workflows.
- Implement CI/CD automation using GitLab pipelines for build, test, and deployment.
- Deploy services and data pipelines in Linux-based environments, ensuring robust monitoring and rollback capabilities.
- Troubleshoot data ingestion or indexing issues and optimize for minimal latency and maximum reliability.
5. Governance, Documentation & Collaboration
- Establish data governance standards to ensure only relevant and useful data is logged and retained in OpenSearch.
- Document system architecture, APIs, data schemas, ETL workflows, and deployment pipelines.
- Work with architects, data scientists, and observability leads to align OpenSearch development with broader platform goals.
- Contribute to the team s knowledge base and technical best practices for maintainability and future scalability.
Required Skills & Experience Core Technical Skills
- Programming Languages: Java, Python, JavaScript, Perl
- Data Engineering: ETL workflow design, data transformation, and ingestion pipeline management
- Search Technologies: OpenSearch (or Elasticsearch), index tuning, query optimization, cluster scaling
- Streaming: Kafka (producers, consumers, schema design, delivery guarantees)
- Version Control & CI/CD: GitLab
- Operating Systems: Linux (shell scripting, deployment automation, monitoring)
Preferred Experience
- Migration of large data volumes from Splunk to OpenSearch or similar observability platform transitions
- Experience managing 100% network data ingestion pipelines or high-throughput log management systems
- Familiarity with data retention and governance best practices for observability data
- Understanding of telecom network operations, monitoring, and telemetry data structures
Soft Skills & Collaboration
- Strong analytical and problem-solving abilities for large-scale data systems.
- Excellent communication and documentation skills to interface with cross-functional teams.
- Ability to work independently while maintaining tight collaboration with onshore and offshore counterparts.
- Proven capability to deliver results under tight deadlines in a dynamic environment.
Success Outcomes
- Successful migration of 100% network data from Splunk to OpenSearch with full operational continuity.
- Optimized OpenSearch clusters delivering faster query performance and reduced data latency.
- Automated, reliable ETL pipelines that improve developer velocity and reduce manual effort.
- Effective data governance only useful, high-value data is logged and retained.
- Reduced licensing and infrastructure costs through efficient OpenSearch utilization.
- Improved observability and insights supporting proactive monitoring and faster issue resolution.
Reporting & Collaboration
- Reports to the OpenSearch Development Lead / Observability Architect.
- Works closely with the Axiom, OneConsole, and SRE/Observability teams.
- Participates in Agile ceremonies (sprint planning, stand-ups, retrospectives) and documentation reviews.
Interview Focus
- ETL and data pipeline design (architecture, throughput, error handling, scaling).
- OpenSearch or Elasticsearch administration and performance tuning.
- Java/Python coding test or live exercise.
- Kafka integration scenarios and troubleshooting.
- Data governance and migration strategy discussions.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.