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Analytics Engineer Jobs

Specialists who build and maintain the data pipelines and models that power business intelligence. A critical role in turning raw data into actionable insights.

Open roles
2
Hiring companies
2
View 2 live roles → Get an alert

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.

What the role does

Inside the role of an Analytics Engineer

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.

  1. 01
    Design and implement data pipelines
  2. 02
    Write and optimise SQL queries
  3. 03
    Test and debug data transformations
  4. 04
    Collaborate with data scientists and business analysts
  5. 05
    Document and maintain data models
  6. 06
    Monitor and optimise data infrastructure performance
Skills & tools

What hiring managers ask for

% of 1 listings posted in the last 12 months that mention each skill, extracted from job descriptions.

dbt
100%
Snowflake
100%
SQL
100%
Data Modeling
100%
Data Quality
100%
Data Pipelines
100%
Metrics
100%
Amplitude
100%
Omni
100%
Career ladder

From Junior to Principal

A typical UK progression for analytics engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.

  1. Level 1

    Junior Analytics Engineer

    0–2 yrs

    Assists in building and testing data pipelines, with a focus on learning and gaining hands-on experience.

  2. Level 2

    Mid-Level Analytics Engineer

    2–5 yrs

    Takes ownership of specific data pipelines and models, ensuring they are robust, scalable, and well-documented.

  3. Level 3

    Senior Analytics Engineer

    5–8 yrs

    Leads the design and implementation of complex data solutions, mentors junior team members, and drives best practices.

  4. Level 4

    Principal Analytics Engineer

    8+ yrs

    Strategises and oversees the entire data infrastructure, influences organisational data strategy, and leads cross-functional projects.

Pathway

How to become a Analytics Engineer

There's no single route, but most people follow some version of these steps.

  1. 1

    Learn the Basics

    Start with foundational skills in SQL, Python, and data warehousing. Gain experience with tools like dbt and Airflow.

  2. 2

    Build Pipelines

    Work on small to medium-sized data pipelines, focusing on data extraction, transformation, and loading (ETL).

  3. 3

    Optimise and Scale

    Refine and optimise existing pipelines for performance and scalability. Begin to take on more complex projects.

  4. 4

    Lead Projects

    Take ownership of large-scale data projects, lead cross-functional teams, and mentor junior engineers.

  5. 5

    Influence Strategy

    Contribute to the overall data strategy of the organisation, driving innovation and best practices.

  6. 6

    Thought Leadership

    Become a recognised expert in the field, contributing to industry standards and influencing the direction of data engineering.

Live jobs

2 live roles

Synthesia logo

Senior Analytics Engineer

As a Senior Analytics Engineer at Synthesia, you will play a crucial role in building and evolving the company's analytics foundations. You will work closely with Product, Analytics, and Engineering teams to transform raw data into trusted datasets and metrics, ensuring data quality and consistency across the organization. This role involves significant ownership and impact, with a focus on scalable and maintainable data models.

Synthesia London, United Kingdom
Remote Permanent

Pricing Analytics Engineer

Pricing Analytics Engineer Consumer PricingBristol Hybrid (2 days per week in office)Competitive SalaryJob Reference J13112An exciting opportunity to join a highly respected consumer-focused organisation within a growing pricing function, where you'll play a key role in supporting pricing strategy through...

Datatech Bristol, Bristol (county), United Kingdom
Hiring locations

Where this role is hiring

The locations with the most live listings for this role today.

London

Location
1 open

Bristol

Location
1 open
FAQs

Common questions

  • 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.

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