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

Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed.

If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future.

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.
• Upskill the Internal Audit department in data analytics techniques, toolings, and AI-driven audit tools.

Technical Competencies & Experience Requirements

Professional Experience

• Minimum 5 years of experience in data analytics, AI governance, model risk auditing, or data platform auditing within a cloud-native tech or financial services platform.
• Hands‑on proficiency with scripting languages (Python, SQL), Big Data technologies (Snowflake, Spark, AWS S3/Redshift) and AI agents (Claude).
• Demonstrated track record of designing automated audit analytics and embedding AI tools into audit methodologies.

Certifications

• Certified Information Systems Auditor (CISA) or Certificate of Cloud Auditing Knowledge (CCAK)
• Certified Data Scientist / Machine Learning Specialist (AWS/GCP/Azure or equivalent)
• Certified Internal Auditor (CIA) highly advantageous

Skills & Competencies

• Strong ability to evaluate complex machine learning architectures and translate technical AI risks into actionable insights for non-technical leadership.
• Forward-thinking mindset with passion for leverage automation, generative AI, and advanced analytics to transform internal controls testing.
• Excellent communication, coaching, and stakeholder management skills across business and engineering units.

Why Ebury?

• Competitive Starting Salary with an annual discretionary bonus that truly rewards your performance from day one.
• Dedicated Mentorship: Learn directly from experienced managers who are invested in your success.
• Cutting-Edge Technology: Leverage state-of-the-art tailor made tools and systems that enable you to perform at your best.
• Clear, Accelerated Career Progression: Defined pathways to leadership and specialist roles within Ebury.
• Dynamic & Supportive Culture: Work in a collaborative environment where teamwork and personal growth are prioritized.
• Generous Benefits Package: Access competitive benefits tailored to your location, which typically include health care and social benefits.
• Central Office: A fantastic location with excellent transport links.

About us

Ebury delivers sophisticated, integrated solutions — business accounts, hedging, and financing — on a single platform with a seamless workflow. Our success is built on a simple premise and singular purpose: To help businesses operate and scale globally.

Since its founding in 2009, Ebury has always been a fast-growing leader in fintech. Today, we bring together 2000+ Eburians across nearly 70 cities and we’re always looking to add to our team.

At the heart of our offering is a proprietary platform, purpose-built to help businesses seamlessly streamline and manage global cash flow. We focus on continuous product evolution and innovation to build the infrastructure for borderless growth and help our clients scale at every stage.

The opportunities at Ebury are as diverse as our people, ranging from business development to engineering roles across our tech pillars.

We believe in inclusion. We stand against discrimination in all forms and are against the intolerance of differences that makes us a modern and successful organisation. At Ebury, you can be whoever you want to be and still feel a sense of belonging no matter your story.

**Important Security Notice for Job Applicants:
**Ebury only accepts applications via official Ebury channels.We will only contact you from an @ebury.com domain. Always check the emails you receive from us, and note that we will never request payment for any part of the recruitment process. Stay safe and report suspicious activity.

**Notice to Recruitment Agencies and Search Firms:
**Ebury does not accept unsolicited resumes, CVs, or candidate profiles from recruitment agencies or search firms without signed written Ebury recruitment terms in place for a specific role. Any unsolicited applications will be considered the sole property of Ebury. Ebury will not be responsible or liable for any placement fees or costs associated with unagreed candidate submissions or subsequent hires.

**AI Transparency Statement:
**Ebury uses Artificial Intelligence (AI) and automated tools to help streamline certain parts of our recruitment process, however, these tools are strictly for administrative efficiency. All hiring decisions, including application reviews, shortlisting, and final selections are evaluated and conducted by human talent acquisition professionals and hiring managers.