Babble is a growth business driven by Customer Experience. Acting as the ultimate Trusted Advisor for cloud-based technologies, we help businesses access the best solutions offered by the world's leading providers.

Solutions for Microsoft Modern Work
Expertise in Cybersecurity
Solutions for Contact Centre Technology
Expertise in Mobile Solutions
Solutions for Communications & Connectivity

Although we serve thousands of customers, we have only begun to realise our potential. Many clients use just one or two of our technologies, creating a significant opportunity to introduce the complete range of our market-leading solutions.

If telecoms excites you and you enjoy an innovative, fast-moving workplace, Babble offers an opportunity to put that enthusiasm to work. Our mission is to become our customers' most trusted advisor for cloud-based technologies, and we are seeking talented, passionate people to strengthen our dynamic team.

As an Analytics Engineer, you will transform raw data into reliable datasets ready for business use, enabling self-service reporting, analytics and informed decisions.

Connecting Data Engineering, Data Product Owner and the business, you will develop and maintain analytical data models in our Snowflake data Lakehouse and curate governed datasets. You will also help maintain and evolve the enterprise semantic layer so that it stays accurate, scalable and straightforward to use. Close collaboration with Data Product Owner, Business Analysts and Business Stakeholders will allow you to turn agreed business definitions into dependable analytical assets supporting OMNI, our enterprise analytics platform.

Develop, implement and maintain dimensional and analytical data models in Snowflake.
Use modern ELT methods to produce reusable datasets prepared for business use.
Build and maintain fact and dimension models for OMNI and broader reporting needs.
Refine analytical models to improve their performance, scalability and ease of use.
Help deliver reliable data products across core business domains.
Introduce data quality checks and validation controls that keep analytical datasets accurate, dependable and suitable for their intended use.

Improve and maintain the context layer and enterprise semantic layer used by OMNI and broader analytical reporting.
Put approved KPI, metric and hierarchy definitions into practice and keep them maintained.
Apply metrics consistently in OMNI and other relevant reporting solutions.
Help manage the performance, governance, documentation and continuing maintenance of context layer and semantic layer components.
Help shape standards and best practices for semantic modelling.
Evaluate and manage how changes to the business or source systems affect analytical models and reporting assets.

Provide curated datasets that make reporting and analysis within OMNI more straightforward.
Facilitate self-service analytics with carefully designed, governed data structures.
Supply BI Developers, Analysts and business users with reliable data products.
Strengthen the consistency, adoption and usability of OMNI as the organisation's strategic analytics platform.

Collaborate with Business Analyst, Data Product Owner and Business Stakeholders to identify analytical needs and opportunities.
Work alongside Data Product Owner to incorporate agreed business definitions into the semantic layer.
Advise on best practices for data modelling, analytics engineering and self-service analytics.
Encourage business adoption of OMNI by providing consistent, dependable analytical datasets.

Experience using context layers to support the semantic layer in modern analytics tools.
Experience delivering work through Agile methodologies.
Experience using Openflow, dbt, FiveTran, Data Factory or equivalent tools.
Experience integrating API and SaaS data.
Experience introducing data quality controls, testing and monitoring.
Experience applying AI to improve coding practices and make data more usable.
Familiarity with development workflows based on Git.

Previous experience as an Analytics Engineer, BI Developer, Data Analyst or in a comparable role.
An advanced level of SQL proficiency.
A solid grasp of dimensional modelling and modern data warehousing principles.
Experience using Snowflake or comparable cloud-based analytical platforms.
Experience with a modern cloud-based data visualisation tool, such as Omni, Tableau, Sigma or a similar solution.
Experience developing and maintaining semantic models and analytical datasets for business users.
Knowledge of ELT and contemporary analytics engineering methods.
Well-developed communication and stakeholder engagement skills.
The ability to convert business requirements into analytical solutions that can scale.

Paid Annual Leave: 20 days of paid holiday.
Paid Public Holidays: 12 paid bank holidays.
Pension Provision: A pension provided in line with statutory requirements.
Statutory Sick Leave: 20 days of statutory sick pay.
Work Pattern: A 10‑day fortnight.
Workplace: A Full‑time position based in the office.
Leave for Parents: Statutory maternity and paternity leave.

We aim to appoint someone promptly while ensuring we choose the right person. Recruitment begins with a screening call. Candidates who progress will attend an interview over Teams, with a possible further interview and competency testing according to the role's requirements.