Data Engineer

WHAT WE DO MATTERS:

Here at The Knot Worldwide, we believe in doing work that matters. In more than 16 countries around the world, The Knot Worldwide’s leading family of brands—including The Knot, WeddingWire, Bodas, The Bash, The Bump, and more—help people take celebration planning from inspiration to action. When you join our global team, you’ll be a part of a diverse group of individuals passionate about serving and enabling our communities to celebrate the moments that make us.

ABOUT THE ROLE AND YOUR TEAM:

The Knot Worldwide’s Data team is looking for a highly motivated, highly energetic team-player with a strong analytical mindset to join as a Data Engineer supporting end-to-end data pipelines for our business.

This role will be partnering closely with our stakeholders and also with other Data teams to develop data models and data-driven solutions that enable deep analysis and self-service analytics for our Business Domains (Product, Marketing and Revenue).

We see a Data Engineer as a hybrid role that combines mostly data engineering skills but also having the ability to pivot through business intelligence or reporting models. You will be responsible for building end-to-end data pipelines using tools like dbt, Airbyte, Airflow and other modern data stack. This role requires proficiency in SQL, python, data modeling, data transformation, data visualization, but also collaboration skills as they play a crucial role in enabling data-driven decision-making within our organization.

The position is based at Wedding Planner’s head office in Barcelona. This position offers the flexibility of working remotely. As a Data Engineer, you will have the opportunity to work from your preferred location (Spain), collaborating with a distributed team of professionals. We embrace a remote-first culture that values work-life balance and provides the necessary tools and resources for effective remote collaboration.

RESPONSIBILITIES:

• Design, build, and maintenance of end-to-end scalable data pipelines to collect, process, and analyze large and complex datasets from various sources, including but not only, website visitors behavioral tracking, customer data, transactional data and other business data using tools like Airbyte, Python and dbt to write mainly SQL-based data transformations and ensure the data is clean and ready for analysis
• Apply dimensional modeling techniques to design tables and views that map business processes into an enterprise data model.
• Develop and support complex ETL infrastructure to ensure the delivery of clean and reliable data to the organization
• Automate manual processes to improve efficiency, robustness, and speed.
• Participate in overall architecture and strategy for the deployment of our end-to-end data pipelines.
• Partner with the rest of Data Platform Engineering Teams to provide business logics to design, develop and move data pipelines into production.
• Assist with performance and tuning of our existing models, pipelines and data-applications.
• Foster data governance practices, ensuring data privacy and security, and documenting data pipelines, transformations, and models, contributing to maintaining a data-driven culture within the organization
• Understand our business and processes including how our data pipelines and data apps support the business processes and apply this knowledge to best solve problems.
• Work and communicate with end users / stakeholders across the organization to understand their needs, providing insights, training them on use of the Information Mart models, data-applications or any actionable results in support of decisions.
• Clearly scope, track, execute, and communicate on projects in an Agile environment.

SUCCESSFUL DATA ENGINEER CANDIDATES HAVE:

• Bachelor’s degree (Computer Science, Engineering, Information Systems or relational functional field)
• 2+ years experience including design, development, data management, administration and support building data models, data pipelines, data warehousing (Snowflake preferred)
• Proficiency in modeling using SQL and dbt, strength in Python
• Understanding of modern data engineering and architecture concepts and practices. This includes knowledge of data warehousing, data pipelines, data marts, and data integration techniques and tools mostly in cloud infrastructure.
• Solid understanding of different business process models and reporting needs and ability to convert requirements into models and end-to-end data pipeline designs.
• Strong organizational and troubleshooting skills with attention to detail, curiosity to detect and explain data anomalies.
• Excellent communication skills, with the ability to explain complex data insights to non-technical stakeholders
• Our international work environment requires fluency in spoken and written English.