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Data Analytics & Observability/ Site Reliability Engineer
- United States
- United States
À propos
We are seeking a highly skilled Site Reliability Engineer (SRE) with a strong focus on Data Analytics, Observability, and Reporting to support and enhance enterprise production systems. This role combines SRE principles with deep expertise in Dynatrace, Client, Power BI, and Snowflake, along with strong knowledge of Oracle and MS SQL Server, to drive system reliability, performance optimization, and proactive incident management. Requirement/Must Have:
Bachelor’s degree or equivalent experience. 5+ years in SRE, DevOps, or Production Support. Responsibilities:
Apply SRE principles (SLIs, SLOs, error budgets) to improve system reliability. Implement proactive monitoring, alerting, and self-healing capabilities. Lead incident response, RCA, and postmortems. Drive continuous improvement in availability, scalability, and resilience. Design and deliver operational dashboards and reports using Power BI. Leverage Client and Dynatrace to analyze logs, metrics, and traces. Correlate data across platforms to identify trends, anomalies, and risk patterns. Use Snowflake, Oracle, and MS SQL Server SQL to query, transform, and analyze operational datasets. Build data models and curated datasets to support reporting and analytics. Translate operational data into actionable insights for engineering and leadership. Administer and optimize Dynatrace (APM, Grail, DQL, synthetic monitoring). Create alerting strategies aligned to SLOs and business priorities. Integrate observability tools with enterprise reporting and ITSM systems. Develop and maintain Power BI dashboards, reports, and semantic models. Integrate Power BI with Snowflake, Oracle, MS SQL Server, Client, and operational data sources. Optimize query performance, data refresh, and dataset design. Implement row-level security and governance controls. Support enterprise reporting standards and governance. Write and optimize SQL across Snowflake, Oracle, and MS SQL Server. Perform cross-platform data analysis and reconciliation. Support data modeling (views, marts, transformations) for analytics. Troubleshoot data performance issues across heterogeneous platforms. Partner with data engineering teams to improve data quality, lineage, and availability. Develop automation using PowerShell (primary), Python, or REST APIs. Build automation workflows for monitoring enhancements, incident enrichment, and data extraction. Create self-service tooling for operations teams. Integrate automation with ServiceNow, schedulers, and observability tools. Integrate monitoring with ServiceNow (incident, event, change management). Automate ticket creation, enrichment, and routing workflows. Ensure alignment with ITIL best practices. Support and optimize Managed File Transfer (MFT) platforms. Monitor and troubleshoot file transfer failures, protocol issues, and throughput. Manage and support enterprise schedulers: Control-M, Stonebranch, Redwood. Analyze batch workflows, dependencies, and SLA adherence. Nice to Have:
Experience integrating Power BI with Snowflake, Oracle, and SQL Server. Strong understanding of cross-platform data architecture and ETL/ELT patterns. Familiarity with Dynatrace Davis AI and automation workflows. Advanced Client data modeling and ingestion optimization. Exposure to Chaos Engineering (e.g., Gremlin). Skills:
Strong knowledge of SRE principles and reliability engineering practices. Hands-on experience with Dynatrace (APM, DQL, observability). Experience with Client (search, SPL, dashboards). Experience with Power BI (data modeling, DAX, performance tuning). Experience with SQL across multiple platforms: Snowflake, Oracle, MS SQL Server. PowerShell automation and scripting. ServiceNow integration. Knowledge of cloud and hybrid architectures. Qualification And Education:
Certifications: Dynatrace, Client, Snowflake, Microsoft (Power BI / SQL Server), Oracle, ITIL.
Compétences linguistiques
- English
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