ERP Lead Data Analyst

Bridge
Nottingham
6 days ago
Applications closed

Related Jobs

View all jobs

ERP Lead Data Analyst

ERP Lead Data Analyst

ERP Lead Data Analyst

I&T Delivery Lead - Carbon / Carbon Data / Oracle ERP

ERP Analyst

Master Data Analyst

ERP Lead Data Analyst

Initial 3 month contract

Outside IR35

Mainly remote, occasional travel to Leeds


The ERP Lead Data Analyst will play a pivotal role in ensuring the success of Phase 0 (an initial phase of work to assess the viability of the business case) of the ERP programme, which focuses on understanding and preparing the data landscape across HR and Finance globally. This individual will lead efforts to identify, map, and assess key data sources, ensuring the groundwork is laid for seamless integration and transformation in subsequent project phases.


This is a hands-on role. During the first three months, the ERP Lead Data Analyst will need to engage closely with stakeholders across the business to gain a deep understanding of the current data landscape—identifying the systems and data in scope, defining key data requirements, and working with the system integrator (SI) to catalogue data while the SI produces the overall strategy. It is critical that whoever takes on this role is a diligent, self-organised professional who understands the importance of data quality, rather than someone who simply operates in a management role.


The exact deliverables will be agreed during initiation but the types of output we would expect to be delivered by this role would be a data inventory, a data mapping document and a data quality assessment.


Key responsibilities

  • Identify and document key data sources across HR and Finance globally, mapping them to ERP requirements.
  • Collaborate with stakeholders to define high-level data cleansing and transformation rules.
  • Conduct an initial assessment of data quality, highlighting risks and gaps.
  • Coordinate with HR and Finance teams to validate assumptions using preliminary data samples.
  • Provide inputs to the overall project plan, defining data-related timelines, risks, and resource needs.

The successful candidate will demonstrate the following:

Skills:

  • Strong data analysis and mapping capabilities, particularly in HR and Finance domains.
  • Effective stakeholder engagement and communication skills.
  • Ability to manage complex data landscapes and identify risks proactively.
  • Organisational skills to coordinate data activities across distributed teams.


Experience:

  • Proven experience in data lead roles within ERP projects, preferably SAP-based implementations.
  • Track record of working on complex, multi-country projects with diverse system landscapes.
  • Experience collaborating with System Integrators (SI) during project discovery and data strategy phases.


Knowledge:

  • Deep understanding of data requirements for HR and Finance processes in ERP contexts.
  • Familiarity with data governance, data quality assessment, and cleansing best practices.
  • Knowledge of global data compliance standards and regulations.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.