Consent Data Analyst

Role Overview

The Consent Data Analyst is responsible for analyzing, interpreting, and operationalizing consent and privacy-related data across the organization. This role bridges business, analytics, and engineering teams to ensure that consent data is accurately captured, governed, transformed, and made available for compliant analytics, marketing, and product use cases.

The analyst plays a key role in supporting a customer privacy–centric data ecosystem, ensuring adherence to regulatory frameworks (e.g., GDPR, CCPA) while enabling data-driven decision-making.

Key Responsibilities

1. Consent & Data Analysis

• Perform end-to-end analysis of consent data lifecycle—from collection to transformation and consumption.

• Analyze large datasets using SQL to identify trends, anomalies, and compliance gaps.

• Conduct data profiling to assess data quality, completeness, and usability for consent-driven use cases.

2. Requirements & Data Modeling

• Gather, document, and translate business requirements into data specifications and analytical solutions.

• Collaborate with data engineers and architects to design dimensional models and consent-focused data structures.

• Review ERDs, data models, and transformation logic to ensure alignment with consent use cases.

3. Consent Platform & Integration Support

• Work with consent management platforms (e.g., OneTrust) and downstream systems (CRM, ESPs, marketing tools).

• Validate and support data pipelines that integrate consent data across platforms.

• Ensure consent data is properly mapped and available across analytics ecosystems.

4. Data Governance, Privacy & Compliance

• Implement and support data governance, lineage, metadata, and quality frameworks for consent data.

• Ensure compliance with privacy regulations (GDPR, CCPA) in all data processes and reporting outputs.

• Partner with data stewards and privacy teams to enforce policies and standards.

5. Data Quality & Issue Resolution

• Identify data quality issues and collaborate with engineering teams to remediate them.

• Develop validation rules and checks for consent data pipelines.

• Monitor data integrity and ensure consistency across systems.

6. Documentation & Best Practices

• Prepare technical specifications for data ingestion, transformations, and analytical outputs.

• Maintain documentation for consent data definitions, lineage, and rules.

• Contribute to analytics standards, templates, and agile best practices.

7. Agile Collaboration

• Participate in Agile ceremonies (stand-ups, sprint planning, retrospectives).

• Work cross-functionally with engineering, product, legal, and marketing teams.

Originally posted on Himalayas