If you’ve been working in a junior data role for a while – building reports, handling spreadsheets, supporting teams – and you’re wondering how to finally get promoted, you’re not alone. This guide explains what mid-level roles involve, why you might be stuck, and how to upskill for free through fully funded training to kickstart a successful career in data analytics.
Understanding the Data Analyst Role
Data analysts turn information into impact. Their job is to collect, clean, and interpret data sets, and then translate this raw data into insights that drive better decisions.
A good data analyst doesn’t just find answers. They know which questions matter.
Here’s what the data analyst job description typically involves:
- Data collection. Data analysts collect data from sources like databases, spreadsheets, surveys, and tracking tools.
- Data cleaning and preparation. They organise and clean the data to remove errors and inconsistencies, so it’s usable and reliable.
- Data analysis. Data analysts use tools like Excel, SQL, Python, and statistical methods to explore and analyse data, uncover trends, and spot what others miss.
- Data visualisation. They create charts, dashboards, or reports that make the story behind the data clear.
- Interpreting the results. Data analysts interpret the findings and turn them into meaningful, actionable conclusions.
- Communicating the findings. They communicate insights to teams and decision-makers through reports, presentations, and data visualisation tools.
Data analysts are needed across every sector: finance, healthcare, tech, retail, marketing, and government. Wherever decisions are made using numbers, skilled data analysts are in demand.
Level up: Four Career Paths for a Data Analyst
The typical data analyst career progression looks something like this:
Intern → Junior Analyst → Mid-Level Analyst → Senior Analyst → Data Analytics Manager
But that’s just one path. As you build experience as a data analyst, you’ll find multiple ways to advance your career, whether you want to specialise, lead, consult, or branch into data science.
Let's take a closer look at four possible career paths available for data analysts.
1. Specialist
Some data analysts choose to go deep, becoming experts in a specific industry or domain. This career path is great if you enjoy mastering how data works in a particular business context.
- Business analysts improve internal processes, systems, or team performance using data.
- Financial analysts help guide investment decisions and manage financial risk.
- Operations analysts optimise performance by fixing structural or technical inefficiencies.
- Marketing analysts, also called market research analysts, use market data to shape campaigns, pricing, and customer targeting.
- Systems analysts use data to match business needs with tech solutions through cost-benefit analysis.
- Healthcare analysts work with patient data to improve care quality and system efficiency.
2. Data Scientist
Many analysts eventually shift into data scientist roles – it's a pivot rather than a straight promotion. Data science focuses more on prediction than description. It often involves building models, writing code, and working with big data sets to power smarter tools and products.
To move into data science, you'd need to:
- Deepen your coding skills (usually Python or R)
- Get comfortable with stats and linear algebra
- Understand core machine learning techniques
This path is for those who enjoy both analysing and building things. If you make the leap, you could go on to become a senior data scientist, ML engineer, or even a chief data officer further down the line.
3. Data Analytics Consultant
If variety, autonomy, and big-picture thinking appeal to you, consulting is a natural next step.
After gaining experience analysing data in-house, many analysts go freelance or join consulting firms to solve data problems across multiple clients and industries. You could be:
- Designing data strategies
- Auditing analytics setups
- Advising on tooling, hiring, or KPIs
It’s not for everyone — you’ll need sharp communication skills and the confidence to guide decisions. But it’s a strong path if you enjoy independence and want to apply your skills in broader contexts.
4. Data Analytics Manager
As mentioned before, a classic career path for data analysts is moving from analysis to leadership.
You start by mentoring juniors or owning bigger projects. From there, you can progress to roles like analytics manager, head of data, or director of analytics. Eventually, you could reach executive roles like chief data officer (CDO).
To succeed here, you’ll need:
- Strategic thinking
- Strong communication
- The ability to advocate for data in the business
Some companies value formal education, such as a master’s degree in data analytics or an MBA. Others care more about your impact and leadership style. Either way, this is a path for those who want to shape teams rather than just charts.
Why People Get Stuck in Junior Roles
The next step in the data analyst career path should be a promotion, but for many data professionals, that step never comes.
If you feel like your title hasn’t changed in years, or you’re always the one “relied on” but never promoted, you’re not alone. Most junior data professionals hit a wall because:
- They never had formal training
- They’re expected to figure it out on their own
- Their role is seen as support, not strategic
The result is that you stay stuck — not for lack of talent, but for lack of recognition and the right growth path.
The good news is, you don’t need a master’s degree or thousands of pounds to move forward. You just need a way to grow that’s built for people already doing the work.
What Mid-Level Data Roles Actually Involve
If you have one or two years’ experience in data analysis and reporting, you’re already doing the work. You just haven’t been given the title (or the pay) yet.
Mid-level data analysts are trusted to:
- Take ownership of data processes rather than just assist others
- Recommend next steps, not just report numbers
- Work with tools like SQL, Python, dashboards, and stakeholder slides
- Collaborate with cross-functional teams
- Communicate findings to non-data people (and influence decisions)
The average UK salary for a mid-level data analyst in 2025 typically ranges from £38,000 to £50,000 per year, depending on your skills, experience, and location.
If you’re already analysing performance, creating reports, or supporting business decisions, you’re halfway there. What’s missing is structure, feedback, and a skill set that helps you think and act more like a mid-level data analyst.
Skills You Need to Move Up
Every company is different, but most mid-level data analysts share a common core skill set:
- A solid grasp of maths and statistics
- Sharp problem-solving skills for sorting through complex data and drawing clear and concise conclusions
- Attention to data quality, accuracy, and consistency
- Programming languages, such as SQL for data management and Python for data analysis
- Good communication skills
That last one is bigger than people think. Mid-level data analysts shape decisions, and that only happens if you can explain your thinking to people who don’t speak data.
Three Ways to Upskill (Without Quitting Your Job)
Want to move up the data analyst career ladder but not sure where to start? You don’t need to leave your role to build momentum.
If you're ready to strengthen your skills in tools like Excel, SQL, Python, Tableau, and Power BI (and become more confident in your data analysis), here are your main options:
The Smart Route: Funded, Flexible, Built for Professionals
There’s a UK government-backed path that gives you everything you need to grow:
- It’s fully funded by your employer (you don’t pay a penny).
- It’s part-time, fully online, and flexible around work.
- You build real skills in data manipulation, data analysis, Python, SQL, data visualisation, and more.
- You enjoy 1:1 support from data experts.
- You build a real portfolio of work.
- You earn a Level 4 Data Analyst qualification (equivalent to a foundation degree).
And the best part? It’s designed for people who don’t necessarily have "data analyst" in their title but work with data every day.
If you’re using Excel, building dashboards, analysing reports, or supporting decisions with data, you may already be eligible.
Next Step: Build Your Data Analytics Career
Ready for career growth? To take the next step in your data analytics career path, start with a quick skills check and see if you qualify for fully funded Level 4 training designed to help you step into a mid-level data role.
Do a Short Skills Audit
Reflect on where you are today. Tick off what you already do and highlight what you want to learn next.
⬜ Using Excel or Google Sheets to report on data
⬜ Building dashboards in Power BI or Tableau
⬜ Presenting insights to your team
⬜ Working with data from marketing, sales, or finance
⬜ Writing basic SQL queries
⬜ Curious about learning Python
⬜ Wanting to feel more confident in your analysis
If you ticked 3 or more, you're not starting from scratch. You're ready to grow.
Check if You Qualify for Free Training
If you’re eligible, you’ll get invited to a short call to help you understand your options and talk to your manager.
Let this be your turning point. Your next title won't come from waiting. It comes from making the next move.