Cyber Managed Services - Data Analyst - IAM Operational Reporting - Senior

EY•Charlotte, NC

2d•$77,500 - $160,500

About The Position

The Cyber Managed Services Data Analyst will consolidate identity and access data across enterprise systems, strengthen operational reporting, and provide timely insights into a client’s access-risk posture. The analyst works with data-source owners, engineers, product owners, architects, and business partners to define data requirements, profile and validate source data, document lineage, and translate business needs into scalable data models and ingestion patterns. The role supports access-governance applications, enterprise controls, remediation activities, and data-driven decision-making. The position involves analyzing and integrating identity and access data from multiple systems, supporting ETL pipelines and reporting datasets, defining data-quality controls, and producing dashboards and analysis that make access risk, control coverage, operational trends, and remediation priorities clear. The analyst also contributes to Agile delivery and maintains requirements, lineage, process, and operating documentation. The role is based in Dallas, Alpharetta, Charlotte, Jacksonville, or San Antonio. EY accepts applications on an ongoing basis.

Requirements

Bachelor’s degree in computer science, information technology, information systems, data analytics, or a related field, or equivalent practical experience.
Approximately 6–9 years of experience in data analysis, systems analysis, business analysis, data engineering support, or a related role.
Demonstrated experience with requirements elicitation, gap analysis, data mining, data profiling, source-to-target mapping, and data-quality assessment.
Strong understanding of dimensional, relational, and unstructured data-modeling concepts.
Experience developing conceptual, logical, and physical data models, including third normal form in relational database environments.
Strong SQL skills and experience with one or more scripting languages such as Python, R, Unix shell scripting, or PL/SQL.
Working knowledge of database and data-platform technologies such as Snowflake, Oracle, and Microsoft SQL Server.
Experience supporting data warehouses, operational data stores, ETL processes, data pipelines, or comparable data-integration solutions.
Ability to combine complex data from multiple systems, identify meaningful trends, and translate findings into clear recommendations.
Experience developing dashboards and data visualizations using Tableau, Power BI, or comparable reporting tools.
Ability to communicate complex data concepts, issues, and recommendations to technical and non-technical audiences.
Strong analytical, problem-solving, documentation, collaboration, and stakeholder-management skills.
Ability to operate effectively in a fast-paced Agile environment with changing business and technology priorities.

Nice To Haves

Experience working with identity and access management, identity governance, cybersecurity, technology risk, or access-control data.
Familiarity with IAM data domains such as identities, accounts, entitlements, applications, credentials, access activity, certifications, and lifecycle events.
Experience with SailPoint IdentityIQ or AccessHub and related access-governance reporting.
Experience with ServiceNow, Jira, Confluence, or comparable workflow and Agile-delivery platforms.
Experience with Snowflake and modern cloud-based data platforms.
Experience using data-modeling or lineage-documentation tools.
Familiarity with graph databases or analytics platforms such as Neo4j.
Experience in a regulated financial-services environment.
Familiarity with audit evidence, control reporting, data governance, and risk-remediation processes.

Responsibilities

Engage with IAM data-source owners and stakeholders to gather requirements, identify authoritative data, and define data needed to support risk-reduction objectives and access-governance processes.
Analyze business and technical requirements and translate them into conceptual, logical, and physical data models that address data quality, performance, lineage, and scalability.
Create, maintain, and scale repeatable data-ingestion patterns supporting operational reporting across thousands of enterprise systems.
Profile, map, reconcile, and validate identity, account, entitlement, credential, inventory, activity, and control-related data from multiple source systems.
Document source-to-target mappings, data lineage, transformation logic, control points, and data-flow diagrams.
Combine data from multiple sources to identify trends, patterns, anomalies, coverage gaps, and actionable IAM risk insights.
Define data-quality rules, metrics, and exception-handling processes; investigate discrepancies and support remediation with source owners and engineering teams.
Write and interpret SQL and scripts to query, manipulate, reconcile, and profile data across cloud and on-premises platforms.
Support engineers in designing and validating ETL pipelines, data transformations, operational data-store structures, and reporting datasets.
Develop requirements, user stories, acceptance criteria, test scenarios, and supporting evidence for new data sources, reporting features, and control enhancements.
Create dashboards, reports, and visualizations communicating access-risk posture, control coverage, data quality, operational trends, and remediation priorities.
Participate in Agile ceremonies, backlog refinement, sprint planning, demonstrations, testing, release readiness, and continuous-improvement activities.
Maintain data dictionaries, requirements documentation, analytical findings, process flows, operating procedures, and stakeholder-ready materials.
Work independently through ambiguity while proactively seeking decisions, clarifications, and support when necessary.