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Data and Analytics

Turning raw data into insight, infrastructure, and intelligence

Overview

Data and Analytics covers the roles that collect, move, transform, store, analyse, and model data across organisations. It is one of the largest and most varied career categories in technology — spanning hands-on data analysis and business reporting through to engineering complex data pipelines, building machine learning models, and designing the architecture of entire data platforms.

The category has three broad orientations. Data engineers and architects build and maintain the infrastructure that makes data available and reliable. Analysts and BI professionals query and interpret data to answer business questions. Data scientists and ML engineers develop statistical models and machine learning systems. Many roles sit at the boundaries between these areas, and SQL is the one skill that runs across almost all of them regardless of specialism.

Roles in this Category

25 roles

Role	Tagline	Outlook
Data Analyst	Querying and interpreting data to answer business questions and support decision-making	Growing	View →
Data Visualization Specialist	Designing data visuals and dashboards that communicate performance and trends clearly	Growing	View →
ETL Developer	Building the pipelines that extract, transform, and load data across enterprise systems	Declining	View →
Business Intelligence Analyst	Building the reports and dashboards that help organisations understand their performance	Stable	View →
Data Architect	Designing the structure of an organisation's data environment at a strategic level	Growing	View →
AI Specialist	Identifying where artificial intelligence creates value and overseeing its implementation	Booming	View →
Spark Developer	Specialising in Apache Spark to build and optimise distributed data processing at scale	Growing	View →
Algorithm Engineer	Designing and optimising algorithms for performance-critical, data-intensive systems	Growing	View →
Analytics Engineer	Transforming raw warehouse data into clean, documented datasets analysts can trust	Booming	View →
NLP Engineer	Building systems that enable machines to understand and generate human language at scale	Booming	View →
Big Data Engineer	Building pipelines and processing systems for data at petabyte-scale volumes	Growing	View →
Elasticsearch Engineer	Building and maintaining search and observability infrastructure on the Elastic Stack	Stable	View →
Data Engineer	Building the pipelines and infrastructure that make data available, reliable, and usable	Booming	View →
Hadoop Developer	Building data processing solutions on the Apache Hadoop distributed computing ecosystem	Declining	View →
Database Administrator	Maintaining the databases that store and serve an organisation's data reliably and securely	Stable	View →
Machine Learning Engineer	Taking machine learning models from experimentation into reliable, scalable production systems	Booming	View →
Data Governance Analyst	Building the frameworks that keep an organisation's data accurate, owned, and trusted	Growing	View →
Computational Scientist	Modelling complex scientific problems using simulation and high-performance computing	Growing	View →
Predictive Analytics Specialist	Building models that forecast business outcomes from churn and demand to fraud and risk	Growing	View →
SQL Developer	Writing and optimising SQL that powers databases, reporting systems, and data pipelines	Stable	View →
Statistician	Applying statistical rigour to design studies and draw reliable conclusions from data	Stable	View →
Data Scientist	Using statistical methods and machine learning to extract insight and build predictive models	Growing	View →
Big Data Architect	Designing the distributed data platforms that handle volume and velocity at enterprise scale	Growing	View →
GIS Analyst	Analysing and visualising geographic data to support location-aware decisions	Stable	View →
Data Warehouse Specialist	Designing and maintaining the warehouse systems that organise data for reporting and BI	Stable	View →

Skills

Hard Skills

SQL
Python
Data Pipeline Orchestration
Statistical Modelling
Data Quality Management
Data Modelling
ETL Pipeline Design
Reporting and Visualisation
Data Governance

Soft Skills

CommunicationTranslating findings for non-technical audiences
Attention to DetailSmall data errors propagate downstream
Analytical ThinkingFraming questions before touching the data
CollaborationWorking across engineering, product, and analytics
Analytical RigourSeparating signal from noise in messy data
Engineering DisciplineBuilding data systems that hold up at scale

Tools & Software

AWSSnowflakedbt SQL ServerApache AirflowPower BIDatabricksJupyter Notebook

Core Themes

Querying, cleaning, and preparing data for analysis or downstream use
Building and maintaining data pipelines and transformation layers
Designing data warehouse, data lake, and lakehouse architectures
Developing dashboards, reports, and visualisations for business stakeholders
Building, training, and deploying machine learning and statistical models
Ensuring data quality, governance, and lineage across the data platform
Working closely with engineering, product, and business teams to make data useful

Typical Entry Points

Data Analyst and SQL Developer are the most accessible entry roles — many practitioners enter through self-study, bootcamps, or degrees in Mathematics, Statistics, Economics, or Computer Science. Google Data Analytics Professional Certificate and Microsoft Power BI certifications are recognised entry credentials. A portfolio of SQL queries, dashboards, or data projects on GitHub is the primary hiring signal for career switchers.

Who This Category Is For

People who enjoy finding patterns and meaning in numbers and datasets
Those who like asking why — not just reporting what the data shows
People from analytical backgrounds (finance, research, economics) considering a tech transition
Those comfortable with ambiguity — data problems are rarely clean or straightforward
People who want a career path with clear progression from analyst to engineer to architect
Those interested in AI and machine learning as a longer-term direction
People who want to be involved in business decisions without being in a pure management role
Those who enjoy writing SQL — it is a daily activity across most roles in this category

Related Categories

Emerging Technologies Software Development Business Systems and Analysis