Intermediate Data Engineer

The Intermediate Data Engineer is a highly motivated and experienced member of the G Adventures data team, responsible for designing, building, and maintaining highly scalable and robust data solutions for our global operations. This role is key in our data‑driven organization, working alongside a team of passionate engineers, developers, analysts, and subject matter experts to deliver solutions that transform the way we use data across the company.

Working with the latest technologies and frameworks, you will leverage your creativity and problem‑solving skills to overcome the challenges of managing large volumes of data in real‑time.

Manage and maintain the automated orchestration and ingestion of data using Fivetran and Airflow MWAA into our Redshift warehouse; assist our BI team by providing support and guidance for our Looker tool; build high‑quality data models using dbt Cloud with a focus on marketing data and utilize Python, SQL, Git, and CI/CD tools to build integrations while maintaining high standards of documentation and coding efficiency.

Design and implement highly scalable, resilient, and performant data solutions that feed into a central data warehouse serving as the single source of truth for the organization. Conform to data architecture methodologies and ensure consistent application. Monitor, maintain, and troubleshoot data pipelines and orchestration to ensure reliable, timely, and accurate ingestion from internal and external source systems. Propose and implement improvements that enhance system performance, scalability, and overall reliability.

Adhere to best practices, coding standards, and design principles to deliver exceptionally clean, efficient, and maintainable data models. Support diagnosing, debugging, and resolving technical issues within a complex data environment involving distributed systems and critical third‑party integrations. Work with the Principal Data Engineer to optimize the data environment, implement methodologies and automated tests, and promote data integrity, accuracy, availability, usability, and security.

Monitor the performance of the data warehouse, diagnose bottlenecks, and optimize resource utilization to ensure scalability for growing data volumes and business requirements.

Work with business stakeholders, infrastructure teams, and technical teams to implement technical solutions for efficient and timely delivery of new data sources. Collaborate with subject matter experts to deliver solutions that enable distribution of data models to BI tools and other data platforms, ensuring compliance with data engineering principles and international regulations. Perform administrative tasks such as license updates and permission changes.

Contribute with code reviews, provide actionable feedback, and mentor other team members. Foster a culture of continuous learning and technical growth. Provide technical guidance to the Data Systems and Guru teams, and contribute to high‑quality documentation for our data environment, including system designs and technical procedures to ensure knowledge transfer.

• University bachelor's degree in computer science, data engineering, or a related technical field, or equivalent extensive practical experience.
• Minimum of 5+ years of professional data engineering experience.
• Advanced SQL knowledge.
• Advanced Python knowledge.
• Experience with ETL tools, particularly Fivetran, and columnar data stores such as Redshift.
• Experience with BI/Analytic tools, Looker experience a plus.
• Experience with a plus, but not required.
• Experience with data modelling using dbt Cloud is a plus, but not required.
• Understanding of data governance principles.
• Experience with major cloud platforms (AWS, Azure, Google Cloud).
• Understanding of data architecture methodologies, such as Medallion, Kimball/Star schema modelling.
• Strong and demonstrated data modelling, data mapping and data analysis experience with meticulous attention to detail.
• Experience with version control strategies and…