IT & Software

Analytics Engineer

Appinio

London · Greater London · United Kingdom

Overview

As Analytics Engineer, you will design and maintain scalable data models and robust data pipelines to enable reliable analytics across the organization. You’ll transform raw data into analytics-ready datasets using SQL, dbt, and Python, and own data quality and documentation. You’ll collaborate with Analytics, Product, Engineering, and business teams to standardize key metrics and ensure a single source of truth. You’ll explore AI-powered tools to automate workflows and prepare the data foundation for AI-driven analytics, contributing to a scalable, trustable data platform.

Pay / Benefits
  • Flexible vacation policy
  • Work from abroad up to 180 days/year (EU)
  • MacBook hardware provided
  • Public transport or mobility budget (Deutschland ticket/NAVIT)
  • Subsidised Urban Sports Club or ClassPass
  • Co-working spaces in major locations
Responsibilities
  • Design, build, and maintain clean, scalable data models in the data warehouse using SQL and dbt
  • Develop and maintain data transformation workflows to create analytics-ready datasets
  • Build and troubleshoot data pipelines and integrations from APIs, databases, and third-party systems
  • Ensure data quality through automated tests, validation, monitoring, and issue resolution
  • Document data models, pipelines, definitions, and transformation logic
  • Define and standardize key business metrics (e.g., revenue, bookings, churn)
  • Collaborate with analysts, stakeholders, and engineering to deliver reliable data solutions
  • Optimize SQL queries, dbt models, and pipelines for performance and scalability
  • Prepare data foundations for AI-driven analytics and AI-powered development workflows
  • Contribute to overall data stack improvement and documentation
Key requirements
  • Strong SQL skills
  • Experience with dbt
  • Proficiency in Python and building data pipelines
  • Data warehousing knowledge with cloud solutions (Redshift, Snowflake, BigQuery)
  • Understanding of data quality, automated testing, validation, and monitoring
  • Ability to translate business requirements into reliable data models and metrics
  • Problem-solving, ownership, and analytical mindset
  • Collaborative communication across technical and non-technical teams
  • Interest in AI-powered tooling and automation
  • Collaboration
  • Communication
  • Proactivity
  • SQL
  • dbt
  • Python

Reference: WJ-747_31056170

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