National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Entry Level Data Analyst

Newham
1 month ago
Applications closed

Related Jobs

View all jobs

Finance Assistant

Maximo/MAS Engineer - consulting

Marketing Executive - Entry-level

Looking for a role within IT....?

EYFS Teaching Assistant

Machine Operative

Are you passionate about data and ready to turn numbers into insights? Our client, a major name in IT and technology, is looking for an Entry Level Data Analyst to join their growing analytics team.

Key Responsibilities:

  • Collect, clean, and analyze data to support business decisions

  • Work on dashboards, visualizations, and reports

  • Identify trends and inconsistencies in datasets

  • Support automation and data processing initiatives

  • Translate business needs into data-driven insights

    Ideal Candidate:

  • Degree in Data Science, Mathematics, Statistics, or related field

  • Strong Excel and basic SQL skills (knowledge of Tableau or Power BI is a plus)

  • Detail-oriented with an analytical mindset

  • Excellent communicator, especially with non-technical teams

  • Curious, motivated, and eager to grow

    What You’ll Get:

  • Real-world project experience

  • Inclusive and collaborative work culture

  • Excellent growth opportunities and benefits

    Ready to build your career in data? Apply today
National AI Awards 2025

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.

LinkedIn Profile Checklist for Data Engineering Jobs: 10 Tweaks to Maximise Recruiter Visibility

As organisations harness vast volumes of data, the demand for skilled data engineers—experts in ETL pipelines, data warehousing, and scalable architectures—has surged. Recruiters routinely search LinkedIn for candidates proficient in tools like Spark, Kafka and SQL pipelines. To stand out, your profile must be optimised for relevant keywords and showcase your technical impact. This LinkedIn for data engineering jobs checklist provides ten precise tweaks to maximise recruiter visibility. Whether you’re building your first data platform or architecting petabyte-scale systems, these targeted adjustments will make your profile attract hiring managers and land interviews.

Part-Time Study Routes That Lead to Data Engineering Jobs: Evening Courses, Bootcamps & Online Masters

Data engineering is at the heart of modern digital transformation. From building scalable ETL pipelines in finance to designing real-time analytics platforms in e‑commerce, organisations across the UK are investing heavily in data infrastructure. As a result, demand for skilled data engineers—professionals who can ingest, process, store and serve vast volumes of data—is soaring. Yet many aspiring engineers cannot pause their careers to study full time. Thankfully, an extensive range of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master's Programmes—allows you to learn data engineering while working. This in-depth guide covers every route: foundational modules and short courses, hands‑on bootcamps, accredited online MScs, plus funding options, planning strategies and a real-world case study. Whether you’re a database administrator, software developer or business analyst aiming to pivot into data engineering, this article will help you map out a tailored path to build in-demand skills without interrupting your professional or personal life.

The Ultimate Assessment-Centre Survival Guide for Data Engineering Jobs in the UK

Assessment centres for data engineering positions in the UK rigorously test your ability to design, build and optimise data pipelines under real-world conditions. Employers use a blend of technical challenges, psychometric assessments, group exercises and interviews to see how you handle data architecture, collaboration and problem-solving at scale. Whether you’re focusing on batch processing, stream engineering or data warehousing, this guide will lead you through every stage with actionable strategies to stand out.