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Lead Software Engineer
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Lead Software Engineer
Virtusa- Posted an hour ago
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Job Description
- Splunk Observability Consultant (Datadog) Experience Minimum 10 years of relevant work experience with monitoring using any product (Dynatrace, Datadog, ELK stack, Splunk, Grafana/Prometheus, etc.), out of which 3 years must be on Datadog in critical production environments. Minimum 5 6 years of work experience in setting up end to end observability covering technical, user experience and business outcome metrics. Experience with AIOps modules Watchdog is an advantage. Experience in SRE implementation, concepts such as SLIs/SLOs and error budgets is key. Designing and building an Observability solution for production class environments. Core Capabilities: Experience in implementing Container, Network, APM, RUM, Log Analytics, end-to-end tracing, and custom alerts with Datadog. Proficiency with containers and related integration of the infrastructure for the observability solution is critical. Ability to configure custom alerts, monitors and build AIOps workflows based on telemetry Good understanding of setting up integration capabilities with other systems via APIs and consuming external APIs as well as ingesting metric-based telemetry via collectors. Ability to design and build custom observability dashboards across different portfolios and personas. Setting up Synthetic Monitoring while integrating its telemetry into the observability stack. Ability to code is preferable Python / Java and Ansible scripting preferred. Qualification: Observability Foundation certification from DevOps Institute or any product level accreditation. Any recognized System Architecture qualifications (eg TOGAF) are a bonus. Role & Responsibilities Architect, design and ensure Implementation of the entire observability solution using Datadog. Clearly segment metrics, logs and traces from the current service indicators. Must also identify any gaps in monitoring and define solutions to improve coverage of the same. Design and implement integrations with COTS.
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Key Skills
About Company
Skills:
data engineering , Data Warehousing, Kafka, Docker, Python, AWS, Apache Spark, Sql, Software Engineering, Gcp, Rest Apis, Azure, Kubernetes, RAG frameworks, Qdrant, MLflow, vector databases, Pinecone, Kubeflow, Cloud MLOps, ETL pipelines, LangChain, Generative AI, LLMs, Clean code practices, prompt engineering, LLM fine-tuning, microservices architecture, Milvus, LlamaIndex
Skills:
Master Data Management (MDM), Data Migration, Performance Tuning, Salesforce Development, Data Governance, Rest Apis, Release management, Middleware platforms, Environment management, Salesforce CPQ configuration, SOAP APIs, Archival implementation
Skills:
Vision-Language Models (VLMs), Python, Visual Components, FlexSim, NVIDIA Omniverse
Skills:
React, Typescript, Docker, PostgreSQL, FastAPI, Python, Sql, Redis, CI CD, AI LLM APIs
Skills:
Hdl, Servicenow, Otbi, Hcm Extracts, Bi Publisher, Security, Oracle HCM Cloud, HSDL, Fast Formulas, SOAP APIs, OIC