Experience - 5 to 15
Location- Kochi, Kerala
Shift- 5 days WFO and Rotational Shift
Your key responsibilities
The I&O Platform Infrastructure Data Analyst collects, processes and analyzes operational data from across EY's infrastructure platforms with a particular focus on HCSP platform telemetry — transforming raw data from workflow orchestration systems, provisioning engines, log aggregation platforms, ITSM tools and capacity management systems into meaningful insights and visualizations.
The role requires a strong analytical skill set combined with sufficient infrastructure and platform automation awareness to understand the context of the data being analyzed. The analyst will serve as the analytical authority for HCSP KPI reporting — tracking metrics such as provisioning SLA attainment, orchestrator failure rates, manual touchpoint reduction, rollback success rates and catalog drift elimination — and will partner with the HCSP engineering team, I&O leadership and service management to drive a data-informed culture of continuous platform improvement.
Skills and attributes for success
- Strong experience designing and delivering data analytics solutions using Power BI, including complex DAX measures, data models and report publishing.
- Proficiency querying and analyzing data from ELK stack (Elasticsearch, Kibana) including KQL query development and Kibana dashboard creation.
- Experience working with large, multi-source operational datasets and transforming them into executive and operational reporting.
- Ability to analyze and report on platform automation data, including:
- Workflow execution metrics
- OPA policy evaluation outcomes and policy compliance trends
- Drift detection signals
- ServiceNow order intake volumes, ticket correlation
- Good understanding of data center infrastructure technologies including:
- Windows Server and Linux operating system fundamentals
- Virtualization platforms — Nutanix AHV, Hyper-V, VMware
- Kubernetes cluster concepts — pods, namespaces, workloads and resource utilization
- Network fundamentals — VLANs, DNS, IP management
- Storage and compute provisioning concepts
- Experience with SQL or KQL for querying structured and semi-structured data sources.
- Experience integrating data from ITSM platforms (ServiceNow or equivalent) into analytical reporting.
- Familiarity with APM and monitoring tooling (Dynatrace, SolarWinds, Prometheus or equivalent) as data sources.
- Experience with ETL/ELT pipelines and data ingestion from multiple infrastructure and platform data sources.
- Scripting capability to automate data extraction and transformation tasks:
- Python (pandas, NumPy, requests)
- PowerShell
- Bash
- Strong written and verbal communication skills — able to present HCSP performance findings and SLA trend analysis to both technical and senior business audiences.
- Strong working knowledge of DevOps, Agile, Kanban, SCRUM and ITIL frameworks.
- Ability to work effectively with global engineering and service management teams across multiple time zones.
To qualify for the role, you must have experience with
- Power BI report and dashboard development — 5–7 years.
- Power BI data modelling, DAX development and Power Query (M) transformations — 5–7 years.
- ELK stack data analysis — Elasticsearch queries and Kibana dashboard development — 3–5 years.
- SQL data analysis and querying against operational data stores — 5–7 years.
- KPI definition, metric design and SLA/OLA reporting for platform or infrastructure services.
- Data integration from ITSM platforms (ServiceNow, Remedy or equivalent).
- Working with infrastructure and platform automation monitoring data — metrics, logs, workflow events and traces.
- Building capacity planning and trend analysis reports for infrastructure and automation platforms.
- Kubernetes and container platform telemetry consumption and analysis.
- Workflow orchestration data analysis — Temporal, Argo or equivalent execution logs and metrics.
- OPA policy evaluation data analysis and compliance reporting.
- Drift detection and configuration audit data analysis.
- Windows Server and Linux operating system concepts — sufficient to contextualize infrastructure data.
- Virtualization platform familiarity (Nutanix AHV, Hyper-V, VMware vSphere or Azure Stack HCI).
- Python scripting for data extraction, transformation and automation — 3–5 years.
- PowerShell scripting for Windows infrastructure data collection.
- Executive reporting and stakeholder presentation delivery.
- Azure Monitor, Log Analytics or equivalent cloud observability data sources (preferred).
- Working with CMDB data to enrich infrastructure and platform analytics (preferred).
