Analytics Engineer
Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 13, 2026.
Why Babble?
Babble is a Customer Experience-led growth business. As the ultimate Trusted Advisor for cloud-based technologies, we specialize in empowering businesses with the best solutions from the world's leading providers.
We are specialists in:
- Microsoft Modern Work
- Cybersecurity
- Contact Centre Technology
- Mobile Solutions
- Communications & Connectivity
With thousands of customers, we're just scratching the surface of our potential. Many of our clients currently benefit from one or two of our technologies, presenting an incredible opportunity to introduce them to our full suite of market-leading solutions.
Join us on this exciting journey and let's achieve greatness together!
About Us | Leading UK Cloud Solutions Provider | Babble
Join Our Dynamic Team a Analytics Engineer
Are you passionate about telecoms? Do you thrive in a fast-paced, innovative environment? At Babble, we’re on a mission to be our customer’s most trusted advisor for cloud-based technologies. We’re looking for passionate and talented individuals to join our dynamic team. If so, we have the perfect opportunity for you!
What will you be doing?
We're looking for an Analytics Engineer to turn raw data into trusted, business-ready datasets that power self-service reporting, analytics, and decision-making.
Working between Data Engineering, Data Product Owner, and the business, you'll design and maintain analytical data models within our Snowflake data Lakehouse, curate governed datasets and support the ongoing maintenance and evolution of the enterprise semantic layer to ensure it remains accurate, scalable, and easy to use. You'll work closely with Data Product Owner, Business Analysts, and Business Stakeholders to translate agreed business definitions into trusted analytical assets that power OMNI, our enterprise analytics platform.
Analytics Modelling
Design, build, and maintain dimensional and analytical data models within Snowflake.
Develop reusable, business-ready datasets using modern ELT practices.
Create and maintain fact and dimension models that support OMNI and wider reporting requirements.
Optimise analytical models for performance, scalability, and usability.
Support the delivery of trusted data products across key business domains.
Implement data quality checks and validation controls to ensure analytical datasets remain accurate, trusted, and fit for purpose.
Semantic Layer, Context Layer & Metrics
Maintain and enhance the context layer and enterprise semantic layer that support OMNI and wider analytical reporting.
Implement and maintain approved KPI, metric, and hierarchy definitions.
Ensure metrics are consistently applied across OMNI and any other relevant reporting solutions.
Support the performance, governance, documentation, and ongoing maintenance of context layer and semantic layer components.
Contribute to semantic modelling standards and best practices.
Assess and manage the impact of business or source system changes on analytical models and reporting assets.
Analytics Enablement
Deliver curated datasets that simplify reporting and analysis across OMNI.
Enable self-service analytics through well-designed and governed data structures.
Support BI Developers, Analysts, and business users with trusted data products.
Improve consistency, adoption, and usability of OMNI as the organisation's strategic analytics platform.
Stakeholder Collaboration
Partner with Business Analyst, Data Product Owner, and Business Stakeholders to understand analytical requirements and opportunities.
Work with Data Product Owner to implement agreed business definitions within the semantic layer.
Provide guidance on data modelling, analytics engineering, and self-service analytics best practices.
Support business adoption of OMNI through trusted and consistent analytical datasets.
Desirable Skills & Experience
Experience working with context layers to support semantic layer in modern analytics tooling.
Experience with Agile delivery methodologies.
Experience with Openflow, dbt, FiveTran, Data Factory or equivalent tooling.
Experience with API and SaaS data integrations
Experience implementing data quality controls, testing, and monitoring.
Experience using AI to improve coding practices and enhance data useability.
Familiarity with Git-based development practices.
Experience as an Analytics Engineer, BI Developer, Data Analyst, or similar role.
Advanced SQL skills.
Strong understanding of dimensional modelling and modern data warehousing principles.
Experience working with Snowflake or similar cloud-based analytical platforms.
Experience working with a modern cloud-based data visualisation tool such as Omni, Tableau, Sigma, or similar.
Experience designing and maintaining semantic models and business-facing analytical datasets.
Knowledge of ELT and modern analytics engineering practices.
Strong stakeholder engagement and communication skills.
Ability to translate business requirements into scalable analytical solutions.
Why work for Babble?
- Annual Leave: 20 days’ paid holiday
- Public Holidays: 12 paid bank holidays
- Pension: Statutory pension provision
- Sick Leave: 20 days’ statutory sick pay
- Working Pattern: 10-day fortnight
- Work Environment: Full-time, office-based role
- Parental Leave: Statutory maternity and paternity leave
The recruitment journey
We want to fill this role quickly, but we want to get the right person. The recruitment process will consist of a screening call. If you proceed past this then you will have an interview over Teams and possibly a follow up interview and competency testing depending on the role requirements.
Direct Candidates Only