Data Analytics Engineer

At Quadient, we support businesses of all sizes in their digital transformation and growth journey, unlocking operational efficiency with reliable, secure, and sustainable automation processes. Our success in delivering innovation and business growth is inspired by the connections our diverse teams create every day, with our clients and each other. It’s these connections that make Quadient such an exceptional place to grow your career, develop your skills and make a real impact – help our future-focused business lead the way in powering secure and sustainable business connections through digital and physical channels. 

Are you passionate about transforming raw data into trusted, business-ready insights?

Quadient is looking for a Data Analytics Engineer to join our Marketing Data & Operations team. In this role, you will design and build scalable data models and pipelines that power dashboards, analytics, and reporting across the organization.

You’ll work at the intersection of data engineering and analytics, helping teams turn complex data from multiple systems into reliable datasets that drive decision-making. The role also plays a key part in the migration of our legacy on-premise platform to a modern cloud data stack.

• Design, build, and maintain analytics-ready data models that power dashboards, reports, and advanced analysis.

• Develop and maintain dbt projects, ensuring high-quality data models, tests, and documentation.

• Build and orchestrate data pipelines using Dagster or similar orchestration frameworks.

• Implement data quality checks and monitoring to ensure accuracy and consistency.

• Optimize pipelines and data models for performance, scalability, and cost efficiency.

• Collaborate with Marketing, Operations, and Analytics teams to define metrics, KPIs, and reporting needs.

• Maintain clear documentation of data models, metrics definitions, and pipeline logic.

• Work closely with IT and data platform teams to align with governance, security, and engineering standards.

• 3–5 years of experience as a Data Engineer, Analytics Engineer, or similar role.

• Strong experience with dbt (data build tool) and analytics data modeling practices.

• Solid understanding of analytical data modeling concepts (facts, dimensions, star/snowflake schemas).

• Hands-on experience with modern cloud data warehouses such as Google BigQuery, Snowflake, or Redshift.

• Experience orchestrating data pipelines using Dagster, Airflow, Prefect, or similar tools.

• Strong SQL skills and familiarity with Git-based development workflows.

• Ability to work cross-functionally with both technical and business stakeholders.

• Master’s degree in computer science, engineering, or a related field.

• Professional English proficiency.

Knowledge gaps can be filled. Even if you don’t satisfy every single requirement or meet every qualification listed, we still want to hear from you.