Analytics Engineer (m/f/d)

ProfilHQ; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

All the hardware you need and your own

Deutschland ticket or mobility budget

Subsidised Urban Sports Club or ClassP

Co-working spaces access

Job summary

Appinio is hiring an Analytics Engineer to join our Data team. You will design and maintain scalable data models, build robust data pipelines, and ensure reliable data for analytics across the organisation.

You will work with SQL, dbt and Python to transform raw data, standardise metrics, and improve data quality. This fully remote role collaborates with teams worldwide and supports AI-enabled analytics initiatives.

Qualifications

• Strong SQL and data modelling experience in a modern data warehouse.
• Practical dbt experience for data transformation, testing and documentation.
• Proficiency in Python and building, maintaining data pipelines across sources.

Responsibilities

• Design, build, and maintain clean, scalable data models in the data warehouse.
• Develop and maintain data transformation workflows from multiple sources.
• Build, maintain, and troubleshoot data pipelines and integrations from APIs and databases.
• Ensure data quality with automated tests, validations and monitoring.
• Document data models, pipelines, and business definitions for transparency.
• Define and standardise business metrics (e.g. revenue, bookings, churn).
• Collaborate with analysts, product and engineering teams to meet data requirements.
• Optimize SQL queries, dbt models, and pipelines for performance.

Skills

SQL

Data modelling

Python

dbt

Data warehousing

APIs integration

Education

Bachelor's degree or equivalent

Tools

dbt

Amazon Redshift

Snowflake

BigQuery

Job description

Allow us to introduce ourselves

Hello there! We’re Appinio, a global market research company that combines an AI-powered insights platform with expert consultancy. On a mission to make the world a little more fact-based, we help companies understand how consumers think and make smarter decisions.

We started out in Hamburg back in 2014, but we’re now humbled to call the world our playground, with over 260 employees spread across 13 countries (we’re remote-first), 2600+ international clients, delivering research from +190 markets, globally.

Want to be a part of the Appinio movement?

Your mission as an Analytics Engineer

We are looking for an Analytics Engineer (m/f/d) with strong data engineering skills to join our Data team and help build a scalable, reliable, and well-structured data foundation across Appinio.

In this role, you will design and maintain clean, scalable data models that make data easy to access, understand, and use across the organisation. You will use SQL, dbt, and Python to transform raw data into meaningful datasets, develop automated workflows, and ensure consistency and reliability across our data warehouse.

Beyond data modelling, you will contribute to building, maintaining, and optimising data pipelines and integrations. You will work with APIs, databases, and third-party data sources to ensure reliable data ingestion, troubleshoot pipeline issues, and improve the overall stability and performance of our data infrastructure.

Working closely with Analytics, Product, Engineering, and business teams, you will help define and standardise key business metrics such as revenue, bookings, and churn, ensuring a single source of truth across the company. You will also take ownership of data quality through automated testing, validation, and monitoring across the data lifecycle.

You will explore and leverage AI-powered tools to improve development workflows, automate repetitive tasks, and enhance data engineering and analytics processes. You will also help prepare our data foundation for AI-driven analytics by ensuring that data models, business definitions, and documentation are structured, consistent, and accessible.

You will contribute to documentation, performance optimisation, and the continuous improvement of our data stack, helping us build a robust and scalable data platform that enables teams across Appinio to make faster, more informed decisions.

What you’ll be doing

• Data Modeling: Design, build, and maintain clean, scalable data models in the data warehouse using SQL and dbt, making data accessible and reliable for analysts and business users.
• Data Transformation: Develop and maintain data transformation workflows, turning raw data from multiple sources into structured, analytics-ready datasets.
• Data Pipelines & Integration: Build, maintain, and troubleshoot data pipelines and integrations, ensuring reliable data ingestion from APIs, databases, and third-party systems into the data warehouse.
• Data Quality & Testing: Ensure data accuracy and reliability by implementing automated tests, validations, monitoring, and proactive issue resolution across data pipelines and models.
• Documentation: Document data models, pipelines, business definitions, and transformation logic to ensure transparency, maintainability, and knowledge sharing.
• Business Logic Ownership: Define, implement, and standardize key business metrics (e.g. revenue, bookings, churn) to ensure consistency across reporting and analytics.
• Collaboration: Work closely with analysts, business stakeholders, and engineering teams to understand data requirements and deliver reliable, scalable data solutions.
• Performance & Infrastructure Optimization: Optimize SQL queries, dbt models, and data pipelines for performance, scalability, and efficient use of data warehouse resources.

You will thrive in this role if

• Strong SQL & Data Modeling Skills: You have excellent SQL skills and hands-on experience designing, building, and maintaining scalable data models in a modern data warehouse.
• Experience with dbt: You have practical experience using dbt to develop, test, document, and maintain reliable data transformation workflows.
• Data Engineering & Python: You are proficient in Python and have experience building, maintaining, and troubleshooting data pipelines, including integrations with APIs, databases, and third-party systems.
• Data Warehousing Knowledge: You understand modern data warehouse architectures and have experience working with cloud-based solutions such as Amazon Redshift, Snowflake, or BigQuery.
• Data Quality & Reliability: You have a strong understanding of data quality principles, automated testing, validation, and monitoring, with a proactive approach to identifying and resolving issues.
• Business Understanding: You can translate business requirements into reliable data models and clearly defined metrics, balancing technical quality with practical business needs.
• Problem-Solving & Ownership: You are analytical, detail-oriented, and comfortable taking ownership of technical challenges, investigating root causes, and developing sustainable solutions.
• Collaboration & Communication: You communicate technical concepts clearly, work effectively with both technical and non-technical stakeholders, and enjoy collaborating across teams.
• AI & Automation Mindset: You are curious about AI-powered development tools and actively explore opportunities to automate repetitive tasks, improve workflows, and increase productivity.

What’s in it for you?

• Flexibility Policy - Average is 30 days taken, however, we do not have a hard cap of number of vacation days as we know life happens
• Temporary work from abroad - If you're based in the EU, you can work outside your country of residence for up to 180 days per year
• All the hardware you need and your own MacBook
• If you are located in Hamburg or Berlin, you'll get a Deutschland ticket or access to a mobility budget with the NAVIT app to get you to and from the office space
• Subsidised Urban Sports Club or ClassPass membership based on location
• In case you’re located in one of the cities where most of our fellow Appinioneers are (Hamburg, Berlin, Munich, London, Madrid, Barcelona, or New York), you can get access to our Co-working spaces

Additional role details

• This is a fully remote position open to candidates based in Germany, the UK, Portugal, the Netherlands, and Spain
• This role will report directly to our Team Lead, Business Intelligence

Our interview process

• Screening Call with the Talent Acquisition team
• Hiring Manager interview
• Case Study
• Executive Interview
• References

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Appinio is an equal-opportunity employer. All applicants will be considered for employment without attention to race, colour, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

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