Specialists who build and maintain the data pipelines and models that power business intelligence. A critical role in turning raw data into actionable insights.
Analytics Engineers are the backbone of data-driven organisations. They design, build, and maintain the data pipelines and models that transform raw data into actionable insights. Working closely with data scientists, business analysts, and product teams, Analytics Engineers ensure that data is clean, reliable, and accessible. This role is crucial in industries ranging from finance and healthcare to e-commerce and technology, where data accuracy and efficiency are paramount.
A typical week for an Analytics Engineer is a mix of coding, testing, and collaboration. They spend time writing SQL and Python scripts, testing data pipelines, and working with cross-functional teams to ensure data integrity and performance.
Based on advertised midpoints across the 19 UK listings priced in pounds in the last 12 months. Base salary only.
% of 12 listings posted in the last 12 months that mention each skill, extracted from job descriptions.
A typical UK progression for analytics engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.
Assists in building and testing data pipelines, with a focus on learning and gaining hands-on experience.
Takes ownership of specific data pipelines and models, ensuring they are robust, scalable, and well-documented.
Leads the design and implementation of complex data solutions, mentors junior team members, and drives best practices.
Strategises and oversees the entire data infrastructure, influences organisational data strategy, and leads cross-functional projects.
There's no single route, but most people follow some version of these steps.
Start with foundational skills in SQL, Python, and data warehousing. Gain experience with tools like dbt and Airflow.
Work on small to medium-sized data pipelines, focusing on data extraction, transformation, and loading (ETL).
Refine and optimise existing pipelines for performance and scalability. Begin to take on more complex projects.
Take ownership of large-scale data projects, lead cross-functional teams, and mentor junior engineers.
Contribute to the overall data strategy of the organisation, driving innovation and best practices.
Become a recognised expert in the field, contributing to industry standards and influencing the direction of data engineering.
The Analytics Engineer will build and maintain data pipelines, develop Power BI reports, and optimize SQL queries to transform business data into actionable insights. This newly created role offers the opportunity to shape a modern data platform and work with Microsoft Fabric, supporting the growth of the analytics function.
This role involves building and managing end-to-end data pipelines using Azure-based tools, developing a lakehouse-style platform with Databricks, and translating business requirements into robust data models. You will also own the semantic and reporting layers in Power BI, enabling self-serve analytics, and play a key role in shaping data standards and practices.
The Energy Analytics Engineer will design and maintain scalable data pipelines using Azure technologies, automate data ingestion from APIs, and develop curated datasets for business intelligence. The role involves close collaboration with cross-functional teams to deliver data solutions that support energy reporting, cost reconciliation, and carbon reporting initiatives. Emphasis is placed on data quality, automation, and enabling non-technical users through training and tool support.
This role involves designing and maintaining data transformations, building scalable data pipelines, and creating trusted datasets to support business intelligence and decision-making. You'll work closely with analysts and stakeholders to translate business requirements into robust data solutions using modern cloud platforms and analytics engineering best practices. The role emphasizes collaboration, data modelling, and enabling data-driven culture across a growing organisation.
This role involves designing and developing interactive DOMO dashboards, building and optimizing ETL/ELT pipelines, and applying advanced analytics to transform complex data into actionable insights. You will collaborate with business and technical stakeholders to define KPIs and ensure high data quality standards.
The locations with the most live listings for this role today.
Essential skills include proficiency in SQL, Python, and data warehousing. Knowledge of ETL tools like dbt and Airflow is also crucial.
Analytics Engineers provide the clean, reliable data that Data Scientists need for their analyses. They collaborate to ensure data is accurate and accessible.
Career progression typically involves moving from hands-on technical roles to leadership positions, influencing data strategy and leading cross-functional projects.
While both roles involve data pipelines, Analytics Engineers focus more on the transformation and modelling of data for business intelligence, whereas Data Engineers focus on building and maintaining the infrastructure.
Salaries for Analytics Engineers can vary widely based on experience and location. For specific salary ranges, please refer to the salary section on this page.
Post your role in 90 seconds and reach the specialist audience that already reads this page.
