Data Analyst, West Midlands

tecnoempleo.com

West Midlands

6 months ago

Applications closed

Related Jobs

View all jobs

Trainee Data Analyst

Data Analyst / Junior Data Scientist

Data Analyst/Junior Data Scientist

Junior Data Scientist / Data Analyst

Data Analyst

Data Analyst Placement Programme

Data Analyst
Job title: Data Analyst
Location : Warwick, UK (Hybrid- 2-3 days/week)
Type: Contract
Client: Wipro

About the Role:
We are seeking a detail-oriented and technically skilled Data Analyst to support our transition from an OpenText SaaS platform to a SharePoint-based data management solution. The ideal candidate will work closely with business stakeholders and technical teams to collate, catalogue, cleanse, and prepare business-critical data for migration. You will play a pivotal role in ensuring data integrity and successful migration through careful planning and coordination.

Key Responsibilities:

Data Collection Collation: Work with stakeholders to gather and consolidate structured and unstructured data from OpenText and other sources.
Data Cataloguing: Develop and maintain a data inventory to document metadata, ownership, and categorization of business content.
Data Cleansing Preparation: Analyze datasets for accuracy, completeness, and redundancy. Identify and resolve data quality issues in preparation for migration.
Migration Planning: Collaborate with IT teams to plan and coordinate the migration of data to SharePoint. Assist in developing mapping, validation, and transformation rules.

Documentation: Create detailed documentation of data processes, standards, and structures to support future data governance.
Stakeholder Communication: Act as a liaison between business units, IT, and external vendors to ensure alignment and clear understanding of migration objectives.
Reporting: Generate regular reports and dashboards to track progress, data quality metrics, and migration readiness.

Qualifications:

Proven experience as a Data Analyst, preferably in enterprise content management or system migration projects.
Strong understanding of data modelling, metadata management, and data lifecycle concepts.
Experience with SharePoint (Online or On-Premise) and familiarity with its data structure and permissions model.
Hands-on experience with OpenText or similar SaaS content platforms is a plus.
Proficiency in Excel, Power BI, or other data analysis and visualization tools.
Excellent analytical, communication, and stakeholder management skills.
Preferred Qualifications:
Experience in migration tools or scripting for data transformation (e.g., PowerShell, Python).
Knowledge of data governance and compliance frameworks.

Python, SharePoint, Power BI,

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

Industry Insights

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

Feb 10, 2026

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Feb 3, 2026

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Jan 23, 2026

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.