Specialist - Data Engineering
LTM · Bengaluru · onsite · Posted today
Undisclosed5–8 yrsfulltimeSourced from
About a minute. You'll make an account on the way through.
About this role
Loaction- C V Raman Nagar Bagmane Bangalore
Experience - 5- 8years
The primary focus of this role is to transform heaps of logs and complex configuration data into highperformance data products You will be responsible for the architectural backbone of our observability platform designing robust parsing mechanisms scalable data pipelines and optimized schemas that power both realtime visualizations and Large Language Model LLM implementations Key Responsibilities Data Parsing Orchestration Build custom parsing logic to extract meaning from complex log strings eg ChassisNo VariantId and Capability parameters Pipeline Schema Design Architect and maintain endtoend data pipelines Create and optimize data schemas that improve the performance and retrieval speed of data products over time Modeling Enrichment Develop sophisticated data models and enrichment layers that connect disparate data points across the ecosystem Visualization To communicate the findings with stakeholders AI Implementation Create Vector Embeddings and buildoptimize RAG RetrievalAugmented Generation layers to interface with LLMs for log summarization and predictive insights Performance Optimization Continuously monitor and slice and dice data structures to reduce latency and improve the accuracy of analyticsdriven insights CrossFunctional Collaboration Translate business challenges into technical data science projects ensuring quality checks and clear communication of technical concepts to stakeholders Candidate needs to travel to client office C V Raman Nagar Bagmane for 2 to 3 days or all days wherever applicable
Experience - 5- 8years
The primary focus of this role is to transform heaps of logs and complex configuration data into highperformance data products You will be responsible for the architectural backbone of our observability platform designing robust parsing mechanisms scalable data pipelines and optimized schemas that power both realtime visualizations and Large Language Model LLM implementations Key Responsibilities Data Parsing Orchestration Build custom parsing logic to extract meaning from complex log strings eg ChassisNo VariantId and Capability parameters Pipeline Schema Design Architect and maintain endtoend data pipelines Create and optimize data schemas that improve the performance and retrieval speed of data products over time Modeling Enrichment Develop sophisticated data models and enrichment layers that connect disparate data points across the ecosystem Visualization To communicate the findings with stakeholders AI Implementation Create Vector Embeddings and buildoptimize RAG RetrievalAugmented Generation layers to interface with LLMs for log summarization and predictive insights Performance Optimization Continuously monitor and slice and dice data structures to reduce latency and improve the accuracy of analyticsdriven insights CrossFunctional Collaboration Translate business challenges into technical data science projects ensuring quality checks and clear communication of technical concepts to stakeholders Candidate needs to travel to client office C V Raman Nagar Bagmane for 2 to 3 days or all days wherever applicable
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Sourced from naukri
Skills
observabilityRetrieval Augmented Generationschemaorchestrationperformance optimizationVisualizationVectorschema designLarge Language ModelparsingEmbeddingsdata modelsLarge Language Models (LLMs)Data StructuresData EngineeringData PipelineData ScienceArtificial Intelligence