Lead Data Analyst

Akkodis is seeking a Data Domain Governance Lead with a client in Charlotte, NC
. Ideally, we are looking for candidates with strong experience with Data Lineage experience, cataloging, data classification channels, tools.

Pay Range: $45-$47/hour;
The rate may be negotiable based on experience, education, geographic location, and other factors.

Full JD:

The Data Domain Governance Lead is responsible for embedding robust data governance practices across Agile delivery teams within banking domain. Operating within a SAFe Agile framework, this role ensures that data standards, models, lineage, privacy, and controls are consistently applied across delivery pipelines. The successful candidate will bring deep expertise in data architecture, metadata management, privacy compliance, and data quality, enabling scalable and audit-ready data ecosystems.

Lead as Domain Data SME, guiding teams on data model standards and ensuring governance while advancing metadata management and data quality standards.

Handle data and analyze it and understand data transformations.

Capturing data through multiple systems, how it is implemented.

Holistic understanding of enterprise data governance processes/policies and to see how they fit into the applications internally.

Data Lineage experience, cataloging, data classification channels, tools. Didn't mention any specific lineage tools so we should be fine on any that are listed in the JD.

Ensure governance guardrails are considered during PI Planning and reflected in Agile Features.

Act as a System Architect and Shared Services SME to support Agile Release Trains (ARTs) in embedding governance principles.

Provide expert guidance to Agile Teams on integrating data governance into delivery workflows and feature design.

Collaborate with Business and Source of Record (SOR) stakeholders to define and maintain domain-level canonical (conceptual) data models.

Review metadata/catalogue entries to ensure critical datasets have clear ownership, lineage, and business semantics.

Support Agile Teams in applying consistent data modelling practices and semantic layer alignment.

Translate EDM policies into domain-specific rules and acceptance criteria.

Partner with delivery teams to embed automated data quality checks and validation rules into data pipelines.

Ensure Features include required data quality controls; contribute to Definition of Done and acceptance criteria.

Guide Agile Teams in embedding lineage capture and metadata tagging within delivery pipelines using modern tooling (e.g., Collibra, Informatica, Alation).

Ensure consistent application of metadata standards and lineage tracking across domains.

Oversee PII and sensitive data classification, labelling, and handling in accordance with data privacy regulations.

Define and enforce archival and retention policies for domain data assets, ensuring compliance and operational efficiency.

Analyse audit findings and feedback to identify gaps and improvement opportunities in data governance practices.

Strengthen domain-level data controls and quality frameworks based on audit insights.

Strong understanding of Treasury and/or Corporate Banking domains, including products, processes, and regulatory requirements.

• Designing conceptual, logical, and physical models for complex financial domains.
• Applying semantic modelling for BI and analytics.
• Knowledge of normalization, denormalization, and performance optimization.
• Hands‑on experience with modelling tools such as ERwin, Power Designer, or equivalent.
• Strong background in enterprise data architecture.
• Hands‑on experience with metadata and lineage tools such as Collibra, Informatica Enterprise Data Catalog, Alation, Microsoft Purview.
• Deep understanding of data privacy regulations and compliance standards and local banking regulations.
• Experience implementing PII classification, data sensitivity labelling, and access controls using tools.
• Knowledge of data archival and retention policies relevant to financial records and audit trails.
• Experience defining and…