What is Data Analytics?
Data analytics is the process of examining, cleaning, transforming, and modelling data to extract useful information, draw conclusions, and support decision-making.
It involves analysing raw data to identify patterns, trends, and insights that can be valuable for businesses, organisations, or individuals. The goal of data analytics is to uncover hidden information, answer questions, and provide a basis for informed decision-making.
Increasingly, data analytics is done with the aid of specialised systems and software, analysing data not only from a mix of sources like internal and external systems but also historic records and new information being gathered.
Data analytics technologies are widely used in commercial industries to help businesses increase revenue, improve operational efficiency, optimise campaigns and bolster customer service efforts, we’re also data analytics enabling the larger organisations we work with to respond quickly to emerging market trends and gain a competitive edge over competition.
There is a wide range of job titles within this specialism given the vast amount of languages, tools and technologies involved in data and analytics.
Types of Jobs in Data Analytics
The most common job titles are:
- Data Analyst
- Data Engineer
- Data Scientist
- BI Developer (Business Intelligence)
- BI Analyst (Business Intelligence)
- Data Architect
- Head of Data
- Data Warehouse Developer
- Database Administrator
Data Analytics job descriptions
Data Analyst
3+ years’ experience
A Data Analyst plays a crucial role in organisations by collecting, processing, and analysing data to help businesses make informed decisions and solve problems. Their primary responsibility is to transform raw data into meaningful insights that can guide strategic actions and improve operational efficiency.
Data Engineer
3+ years’ experience
A Data Engineer is responsible for designing, developing, and maintaining the infrastructure and systems that enable the collection, storage, processing, and retrieval of data in an organisation. Data engineers play a crucial role in the data pipeline, ensuring that data is available, reliable, and accessible for various data-related activities, including data analysis, machine learning, reporting, and business intelligence.
BI Developer
A Business Intelligence Developer is a professional who specialises in designing, developing, and maintaining the technology and systems needed to turn raw data into actionable insights for an organisation.
They will be responsible for data modelling, maintaining ETL (extract, transform, and load) processes, data warehousing, report and dashboard development, data integration, and much more. BI Developers often play a large part in cloud transformation projects within growing organisations.
Data Scientist
A Data Scientist is a professional who uses their expertise in data analysis and various tools and techniques to extract valuable insights and knowledge from data.
Data Architect
A Data Architect designs and builds the structure that holds an organisation's data. They create plans for how data should be organised, stored, and used efficiently to meet the company's needs.
Data Analytics Languages
Given how quickly the technology world is expanding, as well as the ever-changing landscape of data analytics, new languages and tools are being created almost every day.
The most common programming languages we see are:
- SQL (Structured query language)
- Python
- Scala
- ETL (Extract, transform and load)
- ELT (extract, load and transform)
- Microsoft Power BI
- Tableau
- QlikView
- AWS (Amazon Web Services)
- GCP (Google Cloud Platform)
- Azure
Data Analytics Salary Ranges
The salary level for data analytics has fluctuated quite a lot geographically over the years. For the roles below, the ranges we have provided are from junior level to senior – when looking into ‘heads of’ roles and manager roles the salary level tends to be £120k +.
| Job title | Salary range |
| Data Scientist | £60k - £90k |
| Data Engineer | £50k - £90k |
| Data Analyst/BI Analyst | £35k - £50k |
| Database Administrator | £45k - £75k |
| Data Architect | £75k - £115k |
Please bear in mind salaries vary considerably based on experience level and your location, we recommend speaking to one of our data analytics consultants for the latest salary information. Reach out to one of the team here.
Work Environment
Due to the nature of data analytics, predominantly being system-based and little collaboration, the roles are well suited to remote working. We’ve seen working from home (WFH)/Hybrid working being a large part of the overall tech world and it is no different in data.
However, Data Scientists/Analysts and Architects are considered to be more likely to want to spend more time in the office, whereas, engineers and data warehouse developers (the backend teams) tend to want to WFH wherever possible. As there is high demand for this skillset we are seeing employers offering hybrid working models to help secure the best talent in this discipline.
Benefits
Other benefits offered are usually standard within the industry such as:
- Private Healthcare/Dental
- Pension contribution (non-contributory/matched)
- Annual leave (+ ability to purchase/sell additional days)
- Vouchers/allowance for online/personal learning & development
- Gym membership
- Bonus (Discretionary)
- Team Dynamic/Inclusion & Diversity
Teams nowadays are normally working in an “Agile” way, and are composed of Engineers, Scientists and Analysts, with Architects getting involved earlier on in projects in most instances.
The diversity within the Data field has improved a lot recently with the introduction of companies such as Women in Data which gives a lot more promotion for women working in Data. There is still a long way to go when it comes to this area but positive strides are being made.
Career Progression in Data Analytics
There are lots of ways in which those working in data and analytics can progress their careers, and often the CDOs and Head of Data will have worked their way from either a BI background or an Engineering/Scientist/Architect one.
A typical progression route example is below:
Take note that this is a very specific example and there are many ways in which the journey to Head of Data/Head of Data Engineering or Data Science can be completed.
Data Analytics Job Trends
What’s next for job trends within data and analytics? As already mentioned this skill is in high demand with it being recognised recently in our organisation's Digital Leadership Report as the most scarce skill.
The report based on over 2,000 digital leaders responses stated that skills shortages like in data and analytics continue to hamper change with over half of them stating they will increase headcount in this space mostly favouring direct permanent models.
With this in mind where will some of this investment go and what are the trends we’re seeing in this space?
AI
The integration of AI and ML techniques to enhance predictive analytics, automate decision-making processes, and improve overall data analysis capabilities.
Big Data Analytics
The continued growth in the volume, velocity, and variety of data, has led to an increased focus on big data technologies and analytics tools to extract valuable insights from large datasets. Over 61% of our survey respondents stated they had rolled out a small-large scale big data/ analytics implementation.
Cloud-based analytics
The adoption of cloud computing for data storage, processing, and analysis, providing scalability, flexibility, and cost-effectiveness.
Augmented Analytics
The use of AI and ML to automate and enhance data preparation, insight discovery, and the generation of actionable insights.
Summary
Overall the scope of data and analytics as a specialism is proud with multiple disciplines and skills within it. With the emergence of artificial intelligence and machine learning we expect this to influence and develop data and analytics more. The specialisms ability to make businesses more agile and responsive means we’re expecting continued high demand for these roles.
For more insights, advice, or to explore available roles, feel free to get in touch with us via email: Josh.Wilson@HarveyNash.com and Callum.Stephens@HarveyNash.com or LinkedIn, or visit our website for the latest roles and networking events.
Authors
Josh Wilson is a Senior Consultant within the technology specialism team. He is responsible for sourcing leading Data professionals of all levels and providing clients with helpful resources to make informed decisions on their hiring process. Josh manages vacancies including entry-level Data Analysts through to Senior Data Managers in both the permanent and contract market.
Callum Stephens is a Consultant within the technology specialism team. Callum recruits for a variety of different clients within both the public and private sectors. He has experience in hiring for roles such as Data Scientists, BI Analysts or Developers and Data Engineers.
If you’d like to speak further about data, BI and analytics roles then please get in touch.
