Analytics Engineer

Analytics Engineer

Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and build analytical models to drive impactful business decisions.
  • Company: Join Signal AI, a leader in cutting-edge AI technology.
  • Benefits: Inclusive culture, opportunities for growth, and a chance to work with innovative tech.
  • Other info: Diverse perspectives are valued; we encourage everyone to apply!
  • Why this job: Make a real impact by transforming data into actionable insights.
  • Qualifications: Strong SQL and Python skills, experience with ETL processes, and BI tools.

The predicted salary is between 63000 - 77000 £ per year.

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 newly formed Business Analytics team, working closely with Engineering, Operations & Product teams to design & build analytical models for both our premium enterprise clients and internal data users to drive impactful business decisions and enable self-service analytics. The role will need to manage data pipelines, quality and delivery methods across multiple projects. You'll work closely with various stakeholders to understand and identify the correct data for the proper use case. This role should have a strong level of 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 you will be doing?

  • Managing the development and maintenance of ETL pipelines and data models using tools like SQL, dbt, and Airflow.
  • Creating & maintaining interactive dashboards and leading user engagement of them with both our largest clients and internal users in Power BI & Tableau.
  • Transforming, analysing & optimising large sets of quantitative and qualitative data.
  • Taking ownership of reporting processes to ensure accuracy and reliability for the end-users with strong governance and version control.
  • Testing, unpicking & refining areas such as analytical scoring, user behaviour, product performance to identify trends & opportunities and set up the most relevant KPIs.
  • Collaborating with product managers, engineers, and ops analysts to provide data-driven insights from well-designed data models.

Who are we looking for?

  • You have strong expertise in SQL & Python for relational database systems such as Redshift/S3 and SQL Server.
  • You have several years of strong experience with ETL/ELT processes and APIs with tools such as dbt, Airflow, and Talend.
  • You are proficient in using BI visualisation tools, in particular Power BI, Tableau & Metabase.
  • You have good knowledge of data modelling & transformation techniques within data pipelines.
  • 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.

Analytics Engineer employer: SLAMcore

At Signal AI, we pride ourselves on fostering a culture of innovation and collaboration, making us an exceptional employer for those looking to make a meaningful impact in the field of analytics. Our commitment to diversity and inclusion ensures that every voice is heard, while our focus on employee growth provides ample opportunities for professional development in a dynamic environment. Join us in London, where cutting-edge technology meets a supportive community, empowering you to thrive and excel in your career.

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Contact Details:

SLAMcore Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Analytics Engineer

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like SLAMcore!

Show Off Your Projects

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like SLAMcore.

Apply Directly through Our Website

When you find a suitable opening like Analytics Engineer at SLAMcore, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Analytics Engineer

SQL
Python
ETL/ELT Processes
APIs
dbt
Airflow
Talend

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at SLAMcore, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at SLAMcore. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at SLAMcore

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at SLAMcore!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.