Q&A: What's it like to be a Level 3 Data Technician Apprentice?

Written on: 9 April 2021

Written by: Frances Hardcastle

Topic

[Apprentices, Data Technician]

Data is an exciting career path that has recently seen an explosion in demand from employers. If you’re wondering what a career in data could offer you, you’re in the right place!

We ran a Q&A session with Harry Hobbs, our Level 3 Data Technician apprentice to ask him about his role. Harry has been working to support our sales department with data for around four months now, and had already made a big impact!

We asked Harry about his daily tasks and responsibilities as a Data Technician, why data is so appealing as a career path, and how he has been finding the apprenticeship training so far.

Listen to the Q&A below, or scroll down for a written transcript.

A Day in the life of a data apprentice

Harry Data Apprentice Audio Only FINAL

View our Programme: Data Technician Level 3 Apprenticeship

Q: How did you first become interested in a career in data?

A: There’s quite a few things that happened along the way. Firstly, I watched the film The Pursuit of Happyness with my dad as an eleven year old, and I wanted to be a stockbroker. I loved maths in school: in primary school mental maths was my favourite subject.

When I got to 14 or 15, I started to look at accountancy, and did an accountancy apprenticeship. I qualified as an assistant accountant and did that for two years. But I realised it wasn’t really for me.

I still loved maths, and loved the idea of reporting of figures and spotting trends, so thought the natural next step was data. I looked into it, and thought: yeah – I love this.

Q: In a Typical Week, What kind of things does a Data Technician Do?

A: A lot of the stuff I do is actually cleaning and cleansing the data. I read a report last week that said Data Scientists and Data Analysts spend around 60% of their time cleansing data.

To be fair, that sounds quite tedious at first – but I don’t know – I find it quite satisfying to fix up a data set that is riddled with errors and missing data. With a bit of formatting, you can turn it into something you can actually extract value from, which I think is really interesting.

I also do a lot of static trends, which is quite relevant for the sales-adjacent role I’m in. I look at figures now and see how they compared to the previous quarter. I basically see what the differences are, what the trends are, and then I present the data to managers. From there, they can make the relevant business intelligence decisions.

Q: How Does your role fit in with the wider team? Do you get many opportunities to use your initiative, run your own projects and share your ideas?

A: So being a Data Technician as opposed to a Data Analyst, I present a lot of data. I create visuals, dashboards, and lots of interesting stuff. But at this stage, I tend not to do a lot of the actual analysis. I do a little bit at the moment, but this is something I’m working up to.

As I’ve grown into the role and become more familiar with the systems, data and metrics I’m using, I’ve started to get my own questions and my own ideas of things I want to look into.

At the moment I’m looking to backdate productivity statistics over the last 6 months to spot trends, and I’d like to dive into the data around our talent pool to see if I can identify any risk factors for candidates leaving before they can start an apprenticeship.

Q: What Systems and Tools do you use?

A: I use Salesforce for the employer side of things [Salesforce is a Customer Relationship Management system] and then Sunesis for the learner side [an education database]. I cross reference these two systems because the data has to match up and mirror each other.

In terms of tools, I use a lot of Excel, which is great for data. I’m also using Tableau at the moment, but I’m a beginner in that. It’s something I’m trying to train with and improve what I can do with it – it’s a massive tool with lots of potential for data visualisation.

Hopefully in the next 6 to 12 months, I’ll be using Tableau alongside Excel and Salesforce, combining the three and seeing what value I can bring.

Q: What do you enjoy most about working with data?

A: Data’s all around us. It’s everything really. But if you know how to use it, you can drill down into the finest margins and see why things happen. Then you can make changes. You can make microdecisions at the beginning of a process to affect outcomes.

Other than when data is completely invalid or damaged, it rarely lies. To put it concisely, there’s so much opportunity to discover with data, and I just find it really interesting.

Q: What has the Data Apprenticeship Training been like so far?

A: It’s been fascinating. The first course was Data Gathering – basically the fundamentals and foundations of being a Data Technician.

We looked at data types, data sources, the Cloud, file types, structured and unstructured data (and the problems that can come from the latter). It was a great first impression of the theory side of my role.

The next course was Data Analysis and Validation, which was more practical. It looked at validation techniques and how to implement them on Excel, creating visuals, forecasting data, and analysis techniques.

It’s been brilliant so far – there’s a lot I’ve been able to take from the training and use it my role, so that’s fantastic.

Q: Have there been any 'eureka' moments since you started looking at our data?

A: I think the Eureka moment isn’t one specific thing, but just the ability to drill down with more specificity, things like that have just enabled us to have a clearer picture of the data. That in itself has helped decision making. From there, we’ve made better discoveries and helped to change things.

Q: Where do you see yourself in 5 years? Where might a career in data take you?

A: Ideally, I’d like to be an established Data Analyst, working in a team with a few other like-minded data people. That would be really nice.

Q: What advice would you give to someone thinking about a career in data?

A: I think working on your ability to use Excel effectively is massively helpful. I think it’s quite underestimated as a tool, but there’s so much capacity there.

I also think that knowledge of programming languages is very useful, such as R, SQL and Python. I’ve only got basic knowledge of SQL and Python, but they go hand in hand with data analysis.

Ask lots of questions: ask your managers, colleagues, people you work with. They might understand the context of the data better than you because they have more experience – asking questions is great.

I chat to people in the industry on LinkedIn, which can be helpful and read books on the subject. Before starting here, I read a book by Tiffany Bergin called An Introduction to Data Analysis: Quantitative, Qualitative and Mixed Methods. It was a great introduction to the field and thoroughly recommend it.

Find out more:

To learn more about starting a career in data, why not check out our advice from Steve Caughey, the Director of the National Innovation Centre for Data?

If you'd like to know more about a data apprenticeship, you can see our programme information, or search for a data apprenticeship vacancy near you

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