Data Quality Analyst - 2 year FTC

Allianz Management Services Ltd
Guildford
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst – Data Quality & Insights (Hybrid, Glasgow)

Senior Data Analyst – Data Quality & Insights (Hybrid, Glasgow)

Associate Marine Water Quality Data Analyst

Hybrid Marine Water Quality Data Analyst

Data Analyst

Data Analyst – Transformation & Data Quality (Hybrid Edinburgh)

Data Quality Analyst - 2 year FTC

Location:Guildford or Bournemouth (required to be in office 2 days per week)

Salary:Dep on exp + annual bonus + benefits

Who we are

Allianz is a global insurance company serving across 70 different countries, but from the very first day you join our team you’ll know that your contributions are valued. We offer world class learning and career development opportunities, while we celebrate an inclusive culture.

We are seeking a talented and experienced Data Quality Analyst on a 2 year fixed term basis. It is a fantastic opportunity for someone to learn and develop their skills and knowledge as part of the Allianz UK Finance Systems & Change Team. The purpose of this role is to manage the data between our 2 main ERP’s Oracle Financials and SAP, and their connecting upstream and downstream satellite applications.


62574 | IT & Tech Engineering | Professional | Allianz UK | Full-Time | Temporary Warning: When posting this job advertisment on an external job board, the length of the following fields combined must not exceed 3950 characters: "External Posting Description", "External Posting Footer"

Key Accountabilities:

  • The management of system integrations including:
    • ensuring that the integration technology is compliant with Allianz standards and infosec policies,
    • Ensure that there are appropriate reconciliations of accuracy and completeness of data between the ERPs and the satellite system applications and that the reconciliations are performed by the appropriate teams in a timely fashion, as dictated by Financial Controls.
    • subject matter expert level understanding of what financial data is being passed into the ERPs and the purpose of the data and
    • Support the resolution of any data quality issues caused by the integration.
    • Ensure seamless and efficient data flow between systems.
  • This role also controls the accounting integrity and quality of data being passed into the ERPs and will be integral in developing interfaces to and from source systems into the ERPs.

Documentation and Reporting

    • Maintain comprehensive documentation of integration processes, interfaces, and data flows using AZ standards.
    • Prepare regular reports on the status of integrations, compliance checks and data reconciliations.
    • Communicate findings and recommendations to stakeholders and management.

About you

    • Strong understanding of ERP systems, particularly Oracle Financials and SAP.
    • Proficiency in integration technologies and middleware.
    • Strong knowledge of version control software.
    • Experience with data reconciliations and validation processes.
    • Knowledge of infosec policies and compliance standards.
    • Excellent analytical and problem solving skills.
    • Ability to work collaboratively with cross-functional teams.
    • Experience in designing and developing system interfaces.
    • Familiarity with accounting principles and financials data management.
    • Continuous learning mindset to stay updated with the latest integration technologies and best practices.

Qualifications and Experience

    • Educated to GSCE or Batchelors Degree or higher
    • Expert use of MSExcel
    • Experience in designing and developing system interfaces.
    • Experience with data reconciliations and validation processes.
    • Experience in change management and production support.
    • Experience meeting project deliverables
    • Experience in developing new standards, methods, strategies and processes
    • Experience in project testing and implementation, which may include checking results and problem resolution
    • Effectively communicate progress of project work and/or problems to stakeholders
    • Experience in change management and production support

What we will offer you

Recognised and rewarded for a job well done, we have a range of flexible benefits for you to choose from- so you can pick a package that’s perfect for you. We also offer flexible working options, global career opportunities across the wider Allianz Group, and fantastic career development and training. That’s on top of enjoying all the benefits you’d expect from the world’s number one insurance brand, including:

  • Annual bonus scheme
  • 25 days holiday plus bank holidays
  • Contributory pension scheme
  • Life cover
  • Group Income Protection
  • Flexible buy/sell holiday options
  • Flexible working arrangements
  • A discount up to 50% on a range of insurance products including car, home and pet
  • Retail discounts

Our ways of working

Do you need some flexibility with the hours you work? Let us know as part of your application and if it’s right for our customers, our business and for you, then we’ll do everything we can to make it happen.

Here at Allianz, we are signatories of the ABIs flexible working charter. We believe in supporting hybrid work patterns, which balance the needs of our customers, with your personal circumstances and our business requirements. Our aim with this is to help innovation, creativity, and you to thrive - Your work life balance is important to us.

Our Purpose and Values

We secure your future

Be Brave | With Heart | Everyone Counts | Inspiring Trust

Our purpose and values are more than just words on a website - they are the why and how of Allianz. They influence everything we do and guide us how to do it. Created by our people, for our people, they shape our culture, bring us together, and inspire us to be the best. Building an inclusive culture for us all to succeed.

Diversity & Inclusion

At Allianz, we value diversity and inclusion and back this up with our accreditations. Allianz is EDGE certified for gender inclusion, members of the Women in Finance Charter, members of the Stonewall Diversity Champion programme, signatories of Business in the Community’s Race at Work Charter, and an Armed Forces Covenant gold standard employer.

We have a range of employee networks focusing on gender inclusion, cultural diversity, LGBTQIA+, disability and long term health conditions (including neurodiversity), intergenerational and life stages, parents and carers, mental wellbeing, menopause support and armed forces and veterans, all supporting you to bring your best and authentic self to work.

Join us - Let’s Care for Tomorrow

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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 Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.