Analytics Engineer

Data Freelance Hub; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading data solutions provider is seeking an Analytics Engineer in the UK. This role is hybrid and demands 3-5 years of experience in analytics engineering, SQL, and dbt. Responsibilities include data transformation, implementing data quality testing, and collaborating with stakeholders. The company offers benefits like health insurance and flexible work policies, promoting a diverse and inclusive workplace.

Benefits

Flexible on-site and remote policy

Health insurance and wellbeing programs

Latest equipment and office snacks

Access to wellbeing resources and mental health support

Qualifications

• 3-5 years of experience in analytics engineering or related data roles.
• Proven track record of building data models and transformations.
• Experience with cloud data warehouses.

Responsibilities

• Transform raw data into business-ready datasets using dbt.
• Implement comprehensive data quality testing using dbt tests.
• Create data documentation and maintain data catalogs.

Skills

SQL

dbt

Snowflake

Data Quality Testing

Business Intelligence

Data Visualization

Tools

Git

GitHub

Job description

Overview

Analytics Engineer, contract length unknown, pay rate unknown, hybrid remote. Located in the United Kingdom.

Key skills include SQL, dbt, and Snowflake. Requires 3-5 years of experience in analytics engineering and data quality testing.

Position details and context are based on the provided description and may require confirmation from the hiring organization.

What We're Looking For

• Experience & Background
  • 3-5 years of experience in analytics engineering, data analytics, or related data roles
  • Proven track record of building data models and transformations in production environments
  • Experience working with business stakeholders to translate requirements into technical solutions
  • Background in implementing data quality testing and monitoring practices
• Technical Requirements
  • Expert proficiency in SQL and advanced capabilities
  • Hands-on experience with dbt for data transformation and modeling
  • Experience with cloud data warehouses (Snowflake)
  • Experience with data quality testing frameworks (e.g. dbt tests)
  • Proficiency in version control systems (Git, GitHub)
  • Understanding of dimensional modeling concepts and best practices
• Analytics & Business Skills
  • Strong understanding of business intelligence and analytics concepts
  • Experience with data visualization tools and self-service analytics platforms
  • Ability to translate business requirements into technical data solutions
  • Knowledge of statistical concepts and data analysis methodologies

Responsibilities

• Data transformation & Modeling
  • Transform raw data into business-ready datasets using dbt and modern data stack tools
  • Build and maintain dimensional models that serve BI and Product needs
  • Implement business logic and calculations in the data transformation layer
  • Create reusable analytics assets that can be leveraged across multiple use cases
  • Ensure data models follow best practices for performance, maintainability, and scalability
• Data quality & Testing
  • Implement comprehensive data quality testing using dbt tests
  • Develop and maintain data quality monitoring and alerting systems
  • Create data validation rules that catch issues before they impact business decisions
  • Establish data quality metrics and SLAs for analytics datasets
  • Collaborate with all stakeholders to resolve data quality issues at the source
• Analytics enablement
  • Enable self-service analytics by creating intuitive, well-documented data models
  • Partner with business and product stakeholders to understand analytics requirements and translate them into technical solutions
  • Build metric definitions and calculations that ensure consistency across the organization
  • Create data documentation and maintain data catalogs for business and product stakeholders
  • Provide training and support to stakeholders on analytics tools and data interpretation
• Stakeholder collaboration
  • Work closely with analysts and data scientists to provide analysis-ready datasets
  • Collaborate with business stakeholders to understand requirements and design appropriate data solutions
  • Partner with Data Engineers to ensure optimal data pipeline design and performance
  • Communicate technical concepts clearly to both technical and business audiences

About Spendesk

Spendesk is the AI-powered spend management and procurement platform that transforms company spending. It simplifies procurement, payment cards, expense management, invoice processing, and accounting automation, and provides visibility and control across multi-entity structures. Spendesk supports a global user base and operates across several European offices.

Benefits & Culture

• Flexible on-site and remote policy
• Health insurance and wellbeing programs
• Latest equipment and office snacks
• Access to wellbeing resources and mental health support

We are committed to diversity and inclusion and encourage applicants from all backgrounds to apply.

Ready to apply?

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