Carwow.es

Senior BI Analytics Engineer

Carwow.es
Posted 10/21/2026full-timeLondon • United KingdomSeniorWebsite
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Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in analytics engineering with a strong focus on data modeling, SQL proficiency, and experience with dbt and Looker. Capable of translating business requirements into actionable data insights while ensuring data quality and governance.

Highest-signal resume keywords
Analytics Engineering ExperienceExpert-Level SQL SkillsProven Experience With dbtDashboard Development In LookerHands-On Google Cloud Platform Experience

Tech Stack

Tools & technologies
AirflowBigQueryCloudETLGoogle Cloud PlatformSQL

About the role

Key responsibilities & impact
  • Design, build, and maintain scalable data models using dbt on Google Cloud Platform and BigQuery
  • Create and maintain dashboards and explores in Looker for self-serve analytics
  • Translate business requirements into data models, metrics, and visualisations
  • Define and maintain core business metrics and data definitions with stakeholders and the analytics team
  • Implement data quality checks, testing, and documentation within dbt
  • Partner with commercial, product, marketing, finance, and operations stakeholders
  • Optimise query performance and cost efficiency in BigQuery
  • Mentor junior analysts and promote analytics engineering best practices
  • Own the dbt transformation layer and Looker semantic layer
  • Own core business metrics, reporting definitions, data quality and testing frameworks, BI best practices, and documentation standards

Requirements

What you’ll need
  • Previous experience in analytics engineering, BI or data analytics roles
  • Strong expert-level SQL skills; performance tuning experience preferred
  • Experience with modern cloud data platforms and distributed data warehouses, such as BigQuery or Snowflake
  • Proven experience with dbt, including modelling, testing, and documentation
  • Experience building dashboards in Looker
  • Solid understanding of data modelling concepts, including star schema and dimensional modelling
  • Experience working with large-scale datasets
  • Strong communication skills and ability to work with non-technical stakeholders
  • Hands-on Google Cloud Platform experience, especially BigQuery, preferred
  • Experience with orchestration tools such as Airflow preferred
  • Knowledge of data governance and data quality frameworks preferred
  • Exposure to reverse ETL tools such as Hightouch preferred
  • Familiarity with AI coding assistants and integrating them into analytics workflows preferred

Benefits

Comp & perks
  • Hybrid working
  • Competitive salary
  • Matched pension contributions
  • Share options
  • Vitality Private Healthcare
  • Eyecare vouchers
  • Life Assurance
  • Monthly coaching sessions with Spill
  • Enhanced holiday package
  • Bank Holidays
  • 28 days annual leave
  • 1 day for your wedding
  • 1 day off when you move house
  • 30 days of annual leave per year from the third year anniversary
  • 35 days of annual leave per year from the tenth year anniversary
  • Option to buy 3 extra days of holiday per year
  • Work from abroad for a month
  • Inclusive parental, partner and shared parental leave
  • Fertility treatment and pregnancy loss policies
  • Bubble childcare support and discounted nanny fees
  • The latest tech (Macbook or Surface)
  • Up to £500/€550 home office allowance
  • Generous learning and development budget
  • Regular social events
  • Referral bonus

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
SQLData ModelingDbtLookerBigQueryPerformance TuningData Quality ChecksTesting FrameworksDimensional ModelingStar Schema
Soft Skills
Strong Communication SkillsMentoring
Tools & Technologies
Google Cloud PlatformBigQueryAirflowHightouch
Industry Keywords
Data GovernanceData Quality FrameworksSelf-Serve AnalyticsBusiness IntelligenceDistributed Data Warehouses