Data Analyst

Job Title: Data Analyst II

Location: Raleigh, Hybrid (work onsite at Data Centers office or at the client's Tower)

Duration: 12 months

Job Description

Data Quality & Asset Specialist

Job Summary

We are looking for a Data Quality & Asset Specialist to manage the integrity and reporting of our physical and logical infrastructure data within client’s Global Data Center footprint. You will be responsible for ensuring that our data center asset records are accurate, audited, and aligned with our Information Lifecycle Management (ILM) standards. While you work within the Data Center Operations team, your work provides the strategic visibility needed to manage risk and plan for future capacity.

Key Responsibilities

1. Data Quality, Profiling & Auditing

CDE Governance: Monitor and validate Critical Data Elements (CDEs)—including rack utilization, power capacity, and hardware lifecycle dates—to ensure they meet defined quality thresholds.

State of Assets Reporting: Develop and manage a regular cadence of State of the Union reports via Tableau and Google Sheets, providing the Sr. Manager with a clear view of inventory health.

Data Scrubbing: Identify and resolve unidentified assets (equipment that is plugged in but not documented) or orphaned records in the tracking system.

Standardization: Enforce naming conventions and data entry standards across global sites to ensure reporting consistency.

Integrity Reporting: Develop KPIs and dashboards that reflect the health and accuracy of the inventory data.

2. Strategy Support and Planning

ILM Collaboration: Support the ILM Program Manager by implementing data standards and ensuring that the data center’s physical assets comply with broader organizational data lifecycle policies.

Data Stewardship: Act as a Data Steward for infrastructure assets, maintaining high data integrity regardless of the underlying toolset.

Capacity Insights: Provide accurate data on available rack space, power, and cooling to assist in future growth planning.

Cross-Functional Liaison: Serve as the bridge between the boots-on-the-ground DC technicians and the high-level ILM compliance requirements.

3. Risk Management & Mitigation

Identify aging assets that are reaching End of Life (EOL) or End of Service Life (EOSL) to prevent hardware-failure risks.

Root Cause Remediation: Conduct investigations into data drifts and work with the operations team to fix manual entry processes at the source.

Required Technical and “Soft” Skills

Lifecycle Standards: Understanding of industry-standard frameworks for Data Quality and Lifecycle Management (e.g., DAMA or similar), moving beyond simple data entry to true data stewardship.

Google Sheets: Mastery of advanced formulas, pivot tables, and data cleaning techniques

Tableau: Ability to build, maintain, and automate complex data visualizations.

Traits High-grit attention to detail

Possesses a methodical mindset with a high tolerance for repetitive, high-volume tasks. You understand that the macro-level strategy is only as good as the micro-level data, and you take pride in the 'boots-on-the-ground' accuracy required to bridge that gap

Collaborative Stewardship: Strong interpersonal skills to investigate data discrepancies with technicians without assigning blame, fostering a cooperative culture of data accuracy.