HR Data Analyst

Broughton
4 days ago
Applications closed

Related Jobs

View all jobs

Hr Data Analyst

HR Data Analyst

Human Resources Analyst

Employee Benefits Administrator

Data Engineer

AI Scientist

Our client has an opportunity for a HR Analyst to join them on a contract basis until 12th May 2026. You will be working as part of a team responsible for the data analysis and data processing of a broad range of personnel administration related transactions received from internal stakeholders, whilst adhering to Service Level Agreements.

Role: HR Analyst
Location: Broughton, Flintshire. Training for four weeks onsite then the option for hybrid working (2 days a week WFH and 3 days onsite)
Hourly Rate: £21.51 per hour via Umbrella, inside IR35
Clearance: BPSS required to start

What you'll be doing:

Analysis and approval of incoming Personnel Administration changes via the Workday system such as:
External Recruits
Internal Recruits
Termination
Change Job - Change of Location, Change of Working Time, Change of Contract
Organisational Changes
Personal Details Changes
Leave of Absence - Maternity / Adoption / Sabbatical Leave
International Mobility - Transfer In / Transfer Out / International Secondment / Local+
Monitoring the Interface between the Workday and SAP systems
Processing of all Personnel Administration changes via the 'Interface Monitoring Tool' into SAP.
Manual SAP processing of Personnel Administration changes that cannot be processed via the 'Interface Monitoring Tool'.
Manual SAP processing of all peripheral activities to support main Personnel Administration changes such as holiday pay calculations, settlement agreements, Eligibility to Work forms, P45 / Starter Checklist.
Support testing of all future improvements to the Workday tool
Work closely with the Workday Project Team to implement improvements to the Workday tool
Query handling via email and telephone
Requirements:

Experience of data input, data analysis and handling queries is required and preferably within a payroll environment.
Experience of a computerised payroll system - SAP would be preferable
Experience of a computerised personnel administration system - Workday would be desirable
Experience of working in a busy office environment and performing a broad range of administrative duties
Excellent skills in the use of Google Applications
Proven customer service experience both verbal and writtenIf you are interested in applying for this position and you meet the requirements, please apply immediately.

Line Up Aviation has carved its own place in the recruitment of Aviation and Aerospace personnel all over the world for more than 30 years. We work with some of the industry's best-known companies who demand the highest standard of applicants.

Due to the number of applications, we receive, it's not always possible to contact unsuccessful applicants. Unless you hear from us within 14 days of your application, please assume that you have been unsuccessful on this occasion.

"Follow @LineUpAviation on Twitter for all of our latest vacancies, news and pictures from our busy UK Head Office. Interact with us using the #LineUpAviation tag at anytime! Thank you for your follow

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.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.

Machine Learning vs. Deep Learning vs. MLOps Jobs: Which Path Should You Choose?

Machine Learning (ML) continues to transform how businesses operate, from personalised product recommendations to automated fraud detection. As ML adoption accelerates in nearly every industry—finance, healthcare, retail, automotive, and beyond—the demand for professionals with specialised ML skills is surging. Yet as you browse Machine Learning jobs on www.machinelearningjobs.co.uk, you may encounter multiple sub-disciplines, such as Deep Learning and MLOps. Each of these fields offers unique challenges, requires a distinct skill set, and can lead to a rewarding career path. So how do Machine Learning, Deep Learning, and MLOps differ? And which area best aligns with your talents and aspirations? This comprehensive guide will define each field, highlight overlaps and differences, discuss salary ranges and typical responsibilities, and explore real-world examples. By the end, you’ll have a clearer vision of which career track suits you—whether you prefer building foundational ML models, pushing the boundaries of neural network performance, or orchestrating robust ML pipelines at scale.