Analytics Engineer

Appinio

. Design, build, and maintain clean, scalable data models in the data warehouse using SQL and dbt .

Posted 11/9/2026full-timeRemote • Germany, United Kingdom, Portugal, Netherlands, SpainMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in SQL and dbt for designing and maintaining scalable data models and transformation workflows. Proficient in building and troubleshooting data pipelines, with a strong focus on data quality and collaboration with stakeholders.

Highest-signal resume keywords

SQL ExpertiseDbt DevelopmentData Pipeline ManagementCloud-Based Data WarehousingData Quality Assurance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDbtPythonData ModelingData TransformationData Pipeline TroubleshootingAutomated TestingData ValidationPerformance OptimizationBusiness Metrics Definition

Soft Skills

Analytical ThinkingDetail-OrientedTechnical CommunicationCollaborationOwnership

Tools & Technologies

Amazon RedshiftSnowflakeBigQueryAI-Powered Tools

Industry Keywords

Data WarehouseData Quality PrinciplesBusiness IntelligenceAnalytics-Ready DatasetsAPI Integrations

Tech Stack

Tools & technologies

Amazon RedshiftBigQueryCloudPythonSnowflakeSQL

About the role

Key responsibilities & impact

Design, build, and maintain clean, scalable data models in the data warehouse using SQL and dbt
Develop and maintain data transformation workflows that convert raw data into analytics-ready datasets
Build, maintain, and troubleshoot data pipelines and integrations from APIs, databases, and third-party systems
Implement automated tests, validations, monitoring, and proactive issue resolution for data pipelines and models
Document data models, pipelines, business definitions, and transformation logic
Define, implement, and standardize key business metrics such as revenue, bookings, and churn
Collaborate with analysts, business stakeholders, and engineering teams to deliver reliable data solutions
Optimize SQL queries, dbt models, and data pipelines for performance and scalability
Explore AI-powered tools to improve workflows and automate repetitive tasks
Prepare data models, business definitions, and documentation for AI-driven analytics
Report directly to the Team Lead, Business Intelligence

Requirements

What you’ll need

Excellent SQL skills and hands-on experience designing, building, and maintaining scalable data models in a modern data warehouse
Practical experience using dbt to develop, test, document, and maintain reliable data transformation workflows
Proficiency in Python
Experience building, maintaining, and troubleshooting data pipelines, including integrations with APIs, databases, and third-party systems
Understanding of modern data warehouse architectures
Experience with cloud-based data warehouse solutions such as Amazon Redshift, Snowflake, or BigQuery
Strong understanding of data quality principles, automated testing, validation, and monitoring
Ability to translate business requirements into reliable data models and clearly defined metrics
Analytical, detail-oriented, and able to take ownership of technical challenges
Ability to communicate technical concepts clearly and collaborate with technical and non-technical stakeholders
Interest in AI-powered development tools and workflow automation
Application must be submitted in English

Benefits

Comp & perks

Flexibility policy with an average of 30 vacation days taken and no hard cap on vacation days
Temporary work from abroad: EU-based employees can work outside their country of residence for up to 180 days per year
All required hardware, including a personal MacBook
Deutschland ticket or mobility budget via the NAVIT app for employees located in Hamburg or Berlin
Subsidised Urban Sports Club or ClassPass membership based on location
Access to co-working spaces in Hamburg, Berlin, Munich, London, Madrid, Barcelona, or New York