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Join Signal AI as an Analytics Engineer to design and build analytical models that drive impactful business decisions.

Location
London, United Kingdom
Compensation
Not disclosed
Level
mid
Type
full time · On-site

Posted by employer 18 hours ago

First seen on Joblaze 2 hours ago

Last verified on the company career page 2 hours ago

Apply at Signal AI → Save job Scanned from signal-ai.com

What you'll build

  • Manage ETL pipelines and data models
  • Transform and enrich large data sets
  • Create and maintain dashboards
  • Test and refine analytical scoring and KPIs
  • Collaborate with product managers and engineers

Must have

  • Several years of strong experience with ETL/ELT processes
  • Strong expertise in SQL & Python
  • Experience with dbt, Airflow, and Talend

AI in the day-to-day

You are comfortable working with agents and LLMs both internally and as part of the products.

Requirements

Experience
3+ years

Not disclosed in this posting: compensation, visa sponsorship.

Joblaze summary

The Analytics Engineer at Signal AI plays a crucial role in developing and maintaining data pipelines and analytical models that support both enterprise clients and internal users. Proficiency in SQL, Python, and tools like dbt and Airflow is essential for managing ETL processes and creating insightful dashboards. This position is well-suited for someone with several years of experience in data engineering who enjoys translating business logic into structured data flows. The collaborative environment emphasizes iterative development and a proactive approach to problem-solving.

Joblaze insights

  • Listed today — first seen on Joblaze October 27, 2026. Last confirmed on Signal AI's careers page October 27, 2026.
  • This exact title is also open at 1 other location at Signal AI: Lisbon Office.

Quick facts

Is the Analytics Engineer role remote?
No — this is an on-site role in London, United Kingdom.
How much experience is required?
At least 3 years of relevant experience for this Analytics Engineer role.
Where is the role based?
Signal AI is hiring for this position in London, United Kingdom.
What's the tech stack?
Joblaze extracted these technologies from the posting: Airflow, Python, Redshift, S3, SQL, SQL Server.
What seniority level is this role?
Signal AI targets mid-level candidates for this position.
Is this full-time or contract?
Full-time for this Analytics Engineer role at Signal AI.

From the original posting

At Signal AI, we use cutting-edge AI technology to offer clarity on decisions that shape businesses and society. We value restless curiosity, creative thinking, and diverse perspectives as we strive to become AI-native. We believe that AI is a collaborator, not just a tool, and we invite passionate individuals to join us on our journey as we continue to learn, experiment, and grow together.

About the role - what’s your purpose?
We are looking for an Analytics Engineer to join our Business Analytics team, working closely with Engineering and Commercial & Strategic Solutions to design & build analytical models for both our premium enterprise clients and internal data users, driving impactful business decisions and enabling self-service custom insights.
The role will manage data pipelines, quality, and delivery methods across multiple projects, and own how we craft business logic into unique datasets for each client, whether through a dashboard or a more agentic UI. You’ll work closely with stakeholders to understand and identify the best data for each use case. This role requires strong confidence in managing and optimising data models and processes (with and without LLMs) to ensure data products are flexible, pragmatic, and fit for purpose.

Day-to-Day Responsibilities - What will you be doing?

  • Managing the development and maintenance of ETL pipelines and data models using tools like SQL, dbt, and Airflow.

  • Transforming, analysing & enriching large sets of quantitative and qualitative data.

  • Creating & maintaining dashboards & artefacts built on top of pipelines in BI tools or via agents, to deliver key business insights.

  • Testing, unpicking & refining areas such as analytical scoring, user behaviour, product performance to identify trends & opportunities and set up the most relevant KPIs.

  • Taking ownership of meeting client processes to ensure accuracy and reliability for end users, with strong governance and quality testing.

  • Collaborating with product managers, engineers, and ops analysts to provide data-driven insights from well-designed data models.



Who are we looking for?

  • You are confident designing data models, owning semantic layers, and implementing transformation techniques with version control in data pipelines.

  • You enjoy understanding the business logic behind client use cases and translating them into structured data flows.

  • You have several years of strong experience with ETL/ELT processes and APIs with tools such as dbt, Airflow, and Talend.

  • You have strong expertise in SQL & Python for relational database systems such as Redshift/S3 and SQL Server.

  • You are comfortable working with agents and LLMs both internally and as part of the products.

  • You are keen to elevate projects from BI dashboards to agentic workflows.

  • You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so.

  • You love building products as part of a cross-functional team, focused on an iterative, outcome-driven approach.

  • You have strong communication skills and are comfortable expressing your ideas and listening to multiple different audiences.

  • You have a positive attitude and are keen to learn new skills in order to succeed.

Not sure you meet every requirement? Studies show that women and other underrepresented groups often hesitate to apply unless they check every box. At Signal AI, diverse perspectives strengthen our teams, drive innovation, and lead to better performance. So even if your background doesn’t align perfectly with each qualification, we encourage you to apply if you’re passionate about this role.

We're dedicated to creating an inclusive environment where every Signaller feels welcomed, valued, and heard—a place where you can truly thrive as yourself.

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