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Senior Internal Audit Manager - Big Data and AI Strategy for Internal Audit

Ebury Madrid Office - Hybrid: 4 days in the office, 1 day working from home per week

Role Overview

The Senior Internal Audit Manager - Big Data and AI Strategy for Internal Audit is a subject matter expert and strategic lead responsible for embedding advanced analytics, Big Data infrastructure, and Artificial Intelligence into the Internal Audit lifecycle. This role bridges complex data engineering and machine learning principles with internal control evaluation, algorithmic governance, and automated risk monitoring across enterprise platforms.

Qualification Area

Ideal Candidate Specification

Target Experience

5+ years in Data Analytics, AI Governance, or IT Audit specializing in Big Data platforms and Machine Learning models within Financial Services or Tech.

Core Credentials

CISA, CISM, CCAK, or Certified Data Scientist/Engineer credential required; CIA or ACA preferred.

Technical Stack

SQL, Python, R, Snowflake, Databricks, AWS Big Data ecosystem, Spark, Tableau/PowerBI, AuditBoard, Claude.

Regulatory Knowledge

EU AI Act, NIST AI Risk Management Framework, DORA, GDPR, ISO 42001, SR 11-7 Model Risk Management.

Domain Focus

Data pipeline integrity, algorithmic bias, AI transparency, continuous auditing models, and automated testing.

Job Purpose

The Senior Internal Audit Manager - Big Data and AI Strategy for Internal Audit drives the strategy and implementation of AI-driven continuous monitoring, data analytics, and algorithmic audit frameworks. Reporting to the Group Head of Internal Audit, the role provides independent assurance to executive leadership and the Audit Committee on the effectiveness of data governance, machine learning controls, and the integration of Big Data technologies into the audit function.

Key Responsibilities

AI Governance & Algorithmic Assurance

Lead risk-based audits evaluating Machine Learning (ML) models, Artificial Intelligence (AI) implementations, and automated decision-making engines for bias, explainability, and governance compliance.
Assess operational compliance with emerging regulations such as the EU AI Act, NIST AI RMF, and internal model risk management frameworks (e.g., SR 11-7).
Review Generative AI and LLM deployments within internal workflows to ensure data privacy, prompt security, and intellectual property protection.

Big Data Architecture & Data Pipeline Auditing

Evaluate controls across enterprise Big Data infrastructure (e.g., Snowflake, Databricks, AWS Data Lakes), focusing on data lineage, ETL processes, access controls, and data quality.
Conduct technical reviews of automated data pipelines supporting core business operations, financial reporting, and regulatory submissions.

Continuous Audit Automation & Advanced Analytics Strategy

Develop and execute the Internal Audit Big Data & AI roadmap, designing continuous audit techniques to test full population datasets automatically.
Build predictive models, anomaly detection algorithms, and automated audit routines to identify key risk indicators (KRIs) in real time.

Regulatory Alignment & Data Ethics

Audit data protection and privacy mechanisms (GDPR/CCPA) applied within large-scale data storage and analytics environments.
Establish ethical AI evaluation criteria within the internal control framework, addressing data drift, model decay, and algorithmic fairness.

Stakeholder Management & Team Enablement

Partner with Chief Data Officers, Chief AI Officers, Head of Data Engineering, and Data Science leads to provide proactive risk guidance.