About Crystalloids
Crystalloids was founded in 2006 and consists of qualified software and data specialists that help organizations innovate and grow their business by building data-driven solutions. We are a Premier Google Cloud partner. We believe that the foundation for a successful solution is based on three dimensions: the people, the processes and the technology. At Crystalloids we always take these three dimensions into account when we build solutions for our customers.
We have gained a very respectable client portfolio over the years. Our clients operate in market verticals like retail, e-commerce, CPG, media, travel, leisure such as Rituals, KNVB, Body & Fit, FD Mediagroep, ACSI.
What will you do as an Analytics Engineer?
Crystalloids empowers organizations to become truly data-driven by building scalable and efficient data platforms on Google Cloud. In your role as an Analytics Engineer, you’ll operate at the intersection of data engineering and business analytics. This means not only transforming raw data into meaningful insights using tools like dbt, Python, and SQL, but also contributing to core data engineering tasks within the Google Cloud Platform (GCP) ecosystem.
Are you passionate about creating well-modeled, tested, and documented datasets that drive business value? Do you enjoy collaborating with both technical and business stakeholders? If so, we’d love to talk with you!
Main responsibilities and tasks
Data Modeling & Transformation
Design and implement robust data models using dbt to transform raw data into clean, documented, and reusable datasets for reporting and analytics.
Analytics Enablement
Collaborate with stakeholders to understand business logic and requirements, and translate them into technical solutions that are traceable, testable, and version-controlled.
Development and Optimization
Write efficient and maintainable SQL, Python, or an object-oriented language for data transformation pipelines, ensuring performance and scalability on BigQuery and other GCP services.
Data Engineering Responsibilities
Take ownership of data engineering tasks to ensure robust data ingestion and reliable pipeline execution using tools such as Cloud Composer, Cloud Run, Pub/Sub, and Cloud Storage. This includes building and maintaining data pipelines, not just collaborating with Data Engineers.
Testing and CI/CD
Implement "Analytics Engineering as Code" principles, including automated testing, CI/CD pipelines, and version control using Git and Terraform (where applicable).
Documentation & Data Governance
Ensure all transformations and data sets are thoroughly documented to support transparency, reproducibility, and long-term maintainability.
Client Collaboration
Present your work to clients, gather feedback, and help shape data products that meet their business objectives.
Experience and qualifications
Other Requirements:
What we offer