The demand for skilled data analytics professionals has skyrocketed in recent years, making it one of the most sought-after careers in technology and business. Organisations rely on data analysts to interpret data, extract insights, and support data-driven decision-making. Whether you’re looking to become a data analyst, data scientist, or business intelligence analyst, this guide covers everything you need to know about career prospects, skills, salaries, and how to get a job in data analytics.
What Does a Data Analyst Do?
A data analyst collects, processes, and analyses raw data to inform business decisions and can collaborate between multiple departments. They work with large data sets including complex data, use statistical tools, and present data in meaningful ways through data visualisation. Analysts are in high demand across industries, including finance, healthcare, retail, and technology.
Essential Skills for Data & Analytics Professionals
To excel in the field of data analytics, professionals need a combination of technical expertise, analytical thinking, and strong communication skills along with good knowledge of data. As businesses become increasingly data-driven, employers are looking for individuals who can not only work with complex datasets but also derive meaningful insights to drive decision-making. Whether you’re a Data Analyst, Data Scientist, or Data Engineer, these key skills will help you stand out in the industry.
Key Skills:
- SQL – Retrieving, managing, and manipulating data from relational databases
- Data Visualisation – Using tools like Power BI or Tableau to create reports and dashboards
- Proficiency in programming languages – Proficiency in Python or R for data analysis and automation
- Data Cleaning & Preparation – Ensuring accuracy and consistency in datasets
- Statistical Analysis – Understanding data trends, correlations, and predictive modeling
- Machine Learning (for advanced roles) – Building models using libraries like Scikit-learn or TensorFlow
These skills are essential for anyone looking to build a successful career in data and analytics, helping professionals bridge the gap between raw data and strategic decision-making.
What Are the Different Types of Data Analysts?
Data analysts often specialise in various fields depending on the type of data they work with and the industries they serve. Here are some of the common types:
- Business Analyst: Focuses on using sets of data to help businesses make strategic decisions, often involving data visualisation and reporting.
- Marketing Analyst: Specialises in customer and market data, helping businesses improve marketing strategies and understand consumer behaviour.
- Financial Analyst: Works with financial data, helping organisations forecast trends and make informed financial decisions.
- Healthcare Data Analyst: Analyses healthcare-related data to improve patient outcomes, operational efficiency, and regulatory compliance.
- Operations Analyst: Works within a company’s operations team to analyse and optimise processes, reducing costs and improving productivity.
These specialisations often require a combination of industry knowledge and technical expertise.
Data & Analytics Salary Insights
Data analyst salaries vary depending on experience, skill set, location, and industry demand. At Mexa Solutions, we’ve put together a Data & Analytics Salary Guide for 2025, highlighting the growing need for data professionals and the evolving salary trends across various roles. Over the past six months, salary increases have reflected the rising demand for data expertise, driven by rapid advancements in AI, machine learning, and data-driven decision-making.
Our findings show that Data Analysts typically earn between £40,000 and £55,000, depending on specialisation.
Data Engineers see salaries ranging from £40,000 to £75,000, while Senior Data Engineers average salary is between £60,000 and £85,000. Data Scientists earn between £50,000 and £80,000, with Senior Data Scientists making £70,000 to £90,000.
At the higher end, Data Architects receive between £85,000 and £120,000 due to their critical role in designing scalable data solutions.
As the demand for skilled data professionals grows, companies are adjusting salaries to stay competitive. They’re focusing on strategic hiring, creating expert talent pools, and enhancing retention efforts to secure the best candidates.
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Job Outlook for Data Analysts
According to a report by study hub, Data analysis is estimated to be the most promising career for anyone in the 2025-2030 period. With data now being recognised as a key business asset, there is a growing emphasis on the ability to interpret and translate data into actionable insights.
Several key factors are influencing this increased need for data analysts in the UK:
Expanding Use of Data: The UK’s increasing reliance on digital and big data across sectors is creating a wealth of opportunities for data analysts. From improving customer experiences to streamlining operations, businesses are looking for professionals who can help them unlock the potential of the vast data available.
Technological Advancements: The rapid development of artificial intelligence (AI) and machine learning (ML) technologies is transforming industries and increasing the demand for data analysts with expertise in these areas. These advancements enable analysts to work more efficiently, uncover trends, and make data-driven predictions.
Growing Emphasis on Data-Driven Decision Making: More businesses in the UK are adopting data-driven strategies, which involve making decisions based on data analysis rather than intuition alone. As this shift continues, organisations are seeking qualified professionals to provide them with valuable insights and inform their strategic choices.
Government Initiatives and Investment in Data Skills: The UK government is investing heavily in data skills development through initiatives like the National Data Strategy. This push to improve digital literacy and technical expertise is expected to fuel the demand for data analysts as businesses and public sector organisations adopt more sophisticated data practices.
Remote and Flexible Opportunities: Like many countries, the UK is witnessing an increase in remote and flexible work options. Data analysts, in particular, are benefiting from these opportunities, with many companies now hiring professionals from a wider talent pool, including those outside of major urban centres.
With these factors in play, the outlook for data analysts in the UK remains highly positive. Whether you’re just starting in the field or looking to advance your career, the demand for skilled data professionals is set to grow, offering numerous opportunities for those with the right expertise.
Starting a career in data analytics requires a blend of technical expertise and strong analytical abilities. The journey typically begins with gaining a solid educational foundation. A degree in fields like computer science, business analytics, or statistics provides the groundwork for understanding data analysis. However, self-taught individuals with hands-on experience can also successfully break into the field, as practical skills often outweigh formal education.
Once you have a foundation, it’s essential to develop key technical skills. SQL is crucial for querying databases, while programming languages such as Python and R are widely used for statistical analysis and machine learning. Familiarity with data analytics tools like Power BI, Tableau, and Excel is also essential, as these are standard tools in the industry. Additionally, a solid understanding of statistical concepts like probability, hypothesis testing, and regression analysis will greatly benefit your work.
To build your expertise, gaining practical experience is vital. Building a portfolio with real-world projects or contributing to open-source initiatives can significantly enhance your employability. Internships or entry-level roles in analytics are another great way to gain hands-on experience. Alongside this, obtaining certifications like the Google Data Analytics Professional Certificate, Microsoft Certified: Data Analyst Associate, or SAS Data Science Certification can further distinguish you in the job market.
Finally, start applying for entry-level data analyst positions or internships. When preparing your resume, be sure to highlight your technical skills, proficiency with key tools, and ability to communicate insights derived from data. This combination of skills, experience, and certifications will help you launch a successful career in data analytics.
How Mexa Solutions Can Help
Mexa Solutions specialises in data and analytics recruitment, connecting businesses with top professionals in data analysis, data science, and more. With expertise in this rapidly evolving field, Mexa streamlines the hiring process by identifying candidates skilled in key technologies and analytical tools.
Whether you’re a company building a data team or a job seeker looking to advance your career, Mexa offers tailored recruitment solutions to meet your needs, helping businesses stay competitive and empowering professionals with exciting opportunities for growth. Be sure to see see out latest data analytics roles or contact us today to find out more.
Data Analyst FAQs
What is the difference between a Data Analyst and a Data Scientist?
While both roles deal with data, Data Scientists typically focus on building models and algorithms to predict outcomes, while Data Analysts concentrate on interpreting data and producing reports for decision-making.
What is data cleaning, and why is it important?
Data cleaning involves identifying and rectifying errors or inconsistencies in data. It’s crucial because accurate, high-quality data ensures reliable insights and prevents misleading conclusions.