Join EY's Enterprise Technology team as a skilled Infrastructure Data Analyst to enhance global data analytics and reporting capabilities. This role uniquely combines in-depth data analysis with essential infrastructure knowledge, transforming operational data from diverse platforms into actionable intelligence. A primary focus will be supporting EY's next-generation Hyperconverged Service Platform (HCSP), built on Kubernetes, Temporal, and Terraform, by analyzing its performance, reliability, and operational impact across the firm's global data centers.

This position is integral to enabling the platform team to measure success, pinpoint failure patterns, and clearly demonstrate value through data-driven insights.

Collect, process, and analyze operational data from EY's infrastructure, with a special emphasis on HCSP telemetry. Transform raw data from workflow orchestration, provisioning engines, log aggregation, ITSM, and capacity management systems into insightful visualizations.

Serve as the analytical authority for HCSP Key Performance Indicator (KPI) reporting, tracking metrics like SLA attainment, orchestrator failure rates, manual touchpoint reduction, rollback success rates, and catalog drift elimination. Collaborate with the HCSP engineering team, I&O leadership, and service management to foster a culture of continuous platform improvement driven by data.

Demonstrate strong expertise in designing and delivering data analytics solutions using Power BI, including advanced DAX, data modeling, and report publishing. Possess proficiency in querying and analyzing data from the ELK stack, developing KQL queries, and creating Kibana dashboards.

Experience working with large, multi-source operational datasets is crucial for transforming them into executive and operational reports. Ability to analyze platform automation data, including workflow execution metrics, OPA policy outcomes, drift detection signals, and ServiceNow order intake. Foundational knowledge of data center infrastructure, operating systems (Windows Server, Linux), virtualization, Kubernetes, networking, and storage/compute provisioning is essential.

Proficiency in SQL or KQL for data querying, and experience integrating data from ITSM platforms like ServiceNow. Familiarity with monitoring tools (Dynatrace, SolarWinds) and ETL/ELT pipeline development. Scripting skills in Python (pandas, NumPy) and PowerShell for automating data tasks are highly valued. Strong communication skills for presenting findings to technical and business audiences, coupled with a solid understanding of DevOps, Agile, and ITIL frameworks, are required.