Analytics Engineer

Appinio; United States; Teletrabalho; USD 120 000 - 180 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

MacBook provided

Mobility budget / Deutschland ticket

Urban Sports Club or ClassPass

Resumo da oferta

Appinio is seeking an Analytics Engineer to join our data team. You will design and maintain scalable data models, transform raw data into analytics-ready datasets, and ensure a single source of truth across the company.

You will work with APIs, databases, and third-party sources to ingest data, optimize pipelines, and define core business metrics like revenue and churn. This role emphasizes collaboration, automation, and AI-powered tooling to improve workflows.

Qualificações

• Strong SQL & data modeling skills in a modern data warehouse.
• Practical dbt experience for building, testing and maintaining data pipelines.
• Proficient Python for pipelines and automation.
• Understanding of cloud data warehouses (Redshift/Snowflake/BigQuery).
• Knowledge of data quality, testing, validation and monitoring.

Responsabilidades

• Design, build, and maintain scalable data models in the data warehouse.
• Develop and maintain data transformation workflows across sources.
• Build and troubleshoot data pipelines and integrations from APIs and databases.
• Ensure data quality with automated testing, validations, and monitoring.
• Document models, pipelines, definitions, and transformation logic.

Conhecimentos

SQL

Data modeling

dbt

Python

Data warehousing

Data quality

Metrics definition

Collaboration

AI tooling

Ferramentas

dbt

SQL

Python

Descrição da oferta de emprego

Описание:

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? Here at Appinio, we value transparency in our recruitment process, and we've created a blog to share what to expect during each step of our journey together: here.

Задачи:

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.

Обязанности:

• 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 standardise 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.

Требования:

• 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.

Условия:

• 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

Full 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.

Interview process: Screening Call with the Talent Acquisition team, Hiring Manager interview, Case Study, Executive Interview, References.

We ask you to ensure that your application is submitted in English. This post not only outlines our ideal candidate but also serves as an inspiration for what this role can evolve into. Even if you consider yourself an 80% fit but have a genuine passion for this position, we encourage you to apply. We're eager to hear from individuals who share our enthusiasm.

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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