Ness Digital Engineering Careers

Lead Data Analyst

Role Purpose

The Data Analyst will support assessment activities through data discovery, profiling, classification, documentation, and stakeholder engagement. The role serves as the bridge between business, architecture, governance, and technical teams.

Job Summary

The Data Analyst is responsible for identifying where sensitive data exists, understanding how it is used, documenting findings, supporting classification exercises, and validating recommendations. The role will perform detailed analysis of data elements, APIs, interfaces, reports, and downstream systems to provide evidence-based recommendations for governance and remediation.

Key Responsibilities

• Conduct data discovery and profiling activities.
• Support data classification exercises.
• Analyze source and destination data flows.
• Identify sensitive data exposure points.
• Document current-state processes and findings.
• Support data lineage creation.
• Facilitate stakeholder workshops.
• Validate business and technical assumptions.
• Prepare reports, inventories, and assessments.
• Support roadmap and recommendation development.

Required Technical Skills

• Data Analysis
• SQL
• Data Profiling
• Data Mapping
• Data Quality Assessment
• Data Lineage Documentation
• Excel & Reporting Tools
• Metadata Analysis
• Business Analysis

Preferred Skills

• Data Governance
• Privacy Assessment Support
• Data Catalog Tools
• Reporting & Visualization Tools
• Requirements Management

Experience Required

• 5+ years in Data Analysis, Data Governance, or Business Analysis.
• Experience with data assessment or governance programs.
• Experience working with business and technical stakeholders.

Education & Preferred Certifications

Education

• Bachelor's Degree in Information Systems, Computer Science, Business Analytics, or related field.

Preferred Certifications

• CBAP
• CCBA
• CDMP (Associate)
• Data Governance Certifications

Key Deliverables

• Data Inventory
• Data Classification Matrix
• Data Mapping Documentation
• Source-to-Target Analysis
• Data Exposure Findings
• Workshop Outputs
• Assessment Documentation
• Risk Inputs
• Final Assessment Support Artifacts

Key Stakeholders

• Business Teams
• Data Architects
• Security Architects
• Data Engineers
• Application Owners
• Governance Teams

Success Measures / KPIs

• Completeness of data discovery activities
• Accuracy of data classification
• Quality of assessment documentation
• Stakeholder validation of findings
• Timely delivery of analysis outputs