Job Title: Splunk Developer We are looking for 12+ years’ experience Enterprise Observability Engineer, who would leverage powerfully insightful data to inform our systems and solutions, and we’re seeking an experienced pipeline-centric data engineer to put it to good use in building out ETL and Data Operations framework (Data Preparation / Normalization and Ontological processes). Technical Skills Ø Five or more years of experience with Python, SQL, and data visualization/exploration tools Ø Full stack observability lead with Splunk (preferred) / Datadog, Infra monitoring, App onboarding and APM experience Ø Proficiency in observability tools: They are familiar with tools for logging, metrics, and tracing, such as ELK Stack, Splunk and distributed tracing systems. Ø Familiarity with OOB dashboards and templates creation. Trying to integrate ITSI to correlate event data for analytics. Ø Communication skills, especially for explaining technical concepts to nontechnical business leaders Ø General understanding of distributed systems: They need to understand the complexities of modern architectures, including microservices, cloud-native environments, and hybrid infrastructure. Ø Familiarity with the AWS ecosystem, specifically Redshift and RDS Ø Communication skills, especially for explaining technical concepts to nontechnical business leaders Ø Ability to work on a dynamic, research-oriented team that has concurrent projects Ø Experience in building or maintaining ETL processes Ø Experience in insurance domain Ø Professional certification. Ø Strong understanding of distributed systems: They need to understand the complexities of modern architectures, including microservices, cloud-native environments, and hybrid infrastructure. Ø Proficiency in observability tools: They are familiar with tools for logging, metrics, and tracing, such as ELK Stack, Prometheus, Grafana, and distributed tracing systems. Ø Data analysis and visualization skills: They can analyze telemetry data to identify trends and patterns and create visualizations to communicate insights. Ø Scripting and automation: They can automate tasks and create scripts to manage observability infrastructure. Ø Should have experience with cloud platforms like AWS, Azure, and GCP Key Responsibilities And Skill Ø Work with Splunk and internal teams to create a factory model to onboard applications to Splunk Ø Use agile software development processes to make iterative improvements to our back-end systems Ø Model front-end and back-end data sources to help draw a more comprehensive picture of user flows throughout the system and to enable powerful data analysis Ø Build data pipelines that clean, transform, and aggregate data from disparate sources Ø Develop and expand PubSub models and scaling event/messaging architectures Ø Establish and extrapolate Ontological/Semantic standards Ø Develop models that can be used to make predictions and answer questions for the overall business. Ø Designing and Implementing Observability Pipelines: Observability engineers create robust pipelines to collect, aggregate, and analyze data from various sources. Ø Monitoring and ing: They establish monitoring systems and s to detect anomalies and performance issues in real-time. Ø Metric & Instrumentation Standards: Defining common metric standards for every stage of the Application Lifecycle process and Instrumentation standards and scripting including OTel standards alignment Ø Data Analysis and Visualization: They analyze telemetry data (logs, metrics, traces) to gain insights into system behavior and identify trends. Ø Incident Response: They investigate and troubleshoot incidents, using observability data to understand the root cause and implement solutions. Ø Collaboration and Communication: They collaborate with development, SRE, and other teams to ensure observability practices are integrated into workflows and to share insights. Ø Staying Up-to-Date: They stay current with the latest trends in observability, logging, monitoring, and cloud technologies. Ø Documentation and Knowledge Sharing: They create comprehensive documentation for observability systems and processes and share knowledge with other teams .