👩💻 The Role
As an Analytics Engineer at Headout, you will bridge the gap between data engineering and data analysis, creating the foundation for effective data-driven decision making across our organization. At Headout, we firmly believe that well-structured, reliable data is essential for understanding our business and delighting travelers worldwide. Working at the intersection of data infrastructure and business insights, you'll transform raw data into well-defined, documented, and accessible analytical models that empower teams throughout the company. Your technical expertise in data modeling and your understanding of business contexts will be crucial in building a robust analytics ecosystem that drives our global operations and strategic initiatives.
🌟 What makes the role stand out?
Data Foundation Builder
: Design and implement the core data models that power analytics across the organization. Your work will create a single source of truth that teams rely on for consistent, accurate insights.
Technical Craftsmanship
: Apply software engineering best practices to analytics development. From version control and testing to documentation and deployment, you'll bring discipline and quality to our data transformation processes.
Business Domain Translator
: Become fluent in both technical and business languages. You'll translate complex business concepts into clear data structures and metrics definitions that make sense to all stakeholders.
Cross-Functional Enabler
: Your work will empower diverse teams - from Operations and Marketing to Product and Finance - with the data they need to excel. The models you build will support everything from daily operational decisions to strategic business planning.
Analytics Democratizer
: Create self-service analytics capabilities that enable teams throughout the organization to answer their own questions without constantly requiring analyst support.
Modern Stack Innovator
: Work with cutting-edge data technologies to build scalable, efficient data solutions that grow with our business and adapt to changing requirements.
🎯 What skills you need to have
You have a minimum of 2+ years of experience in analytics, data engineering, or related roles, with a focus on data modeling and transformation
Strong SQL expertise is essential, with the ability to write complex queries and optimize data transformations for both accuracy and performance
You possess a strong business acumen that helps you understand the context and importance of the metrics you're defining and modeling
Experience with modern data transformation tools and methodologies (
dbt, Airflow
,
Prefect
or similar tools) and understanding of data modeling concepts (dimensional modeling, star schemas, etc.)
You have a keen eye for data quality and testing methodologies to ensure reliable analytics outputs and are familiar with how to apply software development best practices to analytics code
Your communication skills enable you to collaborate effectively with both technical and business stakeholders to translate requirements into well-structured data models
Experience with data visualization tools (Looker, Tableau, Power BI) is beneficial for understanding the end-user needs
Knowledge of Python or other programming languages is a plus for extending analytics capabilities beyond SQL.