Senior Customer Marketing Data Analyst

Company Description

Hi! We’s UW. We’re on a mission to take the headache out of utilities by providing them all in one place. One bill for energy, broadband, mobile and insurance and a whole lot of savings!

We’re aiming to double in size as we help more people to stop wasting time and money. Big ambitions, to be delivered by people like you.

Got your attention? Read on…

We put people first. It’s all about you..

We're looking for an experienced Senior Marketing Data analyst to join our team to work closely with our Customer Marketing team. Your work will directly inform campaign design, performance tracking, and long-term marketing effectiveness. You'll help shape the marketing strategy through data – identifying what works, what doesn’t, and what could.

This role is hands‑on and embedded within cross‑functional teams, requiring a strong foundation in data modelling, advanced SQL, and providing tailored insights to stakeholders.

We deliver progress. What you’ll do and how you will make an impact.

As a Senior Data Analyst at Utility Warehouse, you will be designing and developing the system of tables within a specific domain. This role is responsible for ensuring that the data model remains coherent, scalable, and cost‑effective.

You will act as a technical lead and strategic partner to our core business units. You will be responsible for eliminating technical debt in our data stack and driving the adoption of advanced analytics methodologies. This role operates at the intersection of engineering and business strategy, requiring you to translate ambiguous business problems into actionable insights and scalable technical solutions.

This role will work directly with the Customer Marketing team. Your work will directly inform campaign design, performance tracking, and long‑term marketing effectiveness. You'll help shape the marketing strategy through data – identifying what works, what doesn’t, and what could.

Your responsibilities will include:

• Analytics Engineering (Dataform/dbt): Build and maintain end‑to‑end analytics‑ready data models in Dataform, independently handling complex logic and transformations.
• CI/CD & Dev Ops (Data version control): Apply version control (through tools like Git & Github) and unit testing practices to analytics models, to ensure data assets are stable, reproducible, and ready for deployment.
• Performance Engineering: Write optimised SQL, proactively tuning for performance (cost & runtime) and addressing alerts about data quality.
• Ownership: Independently plan and execute medium‑to‑large requests through to completion; identify and proactively address tech debt.
• Actionable Insight: Translate complex data into actionable business and marketing insights. Move beyond "what happened" to explain "why it happened" and recommend "what to do next."
• Dashboards/Reporting: Build visual self‑serve dashboards and reports for users to access KPIs / metrics and explore/analyse pre‑built data set.
• Stakeholder Management: Manage the full request lifecycle. Actively engage with stakeholders to refine broad requests into clear requirements, providing accurate estimations and delivering within agreed timelines.
• Domain Ownership: Develop deep knowledge of customer marketing. Understand the impact of key metrics on the business and participate in defining team goals based on this knowledge.

To be successful in this role you’ll need:

• Technical Mastery:

  • SQL Proficence (Expert)-You can debug the most complex queries.

  • Advanced data modelling skills:
    You can develop and implement sophisticated, reusable and scalable, domain‑level data models. You design for scale and architect dimensional data models that support multi‑year business scalability

  • Technical Standards (Governance):
    You can evidence that you have influenced technical guidelines, principles and standards. You conduct rigorous code reviews and ensure only high‑quality code enters production.

  • Analytics Methodology:
    Strong working knowledge of advanced analytics methodologies (e.g. attribution modeling, cohort analysis methods) implemented directly into data models.

  • Customer Marketing Tech Stack:
    Familiarity with customer…