Job Description
Impress is a fast-growing med-tech company modernizing orthodontic care through advanced, doctor-led clear aligner treatments . We help people achieve a healthy and confident smile through a seamless, technology-driven patient journey.
We operate across three major regions — the US, UK, and EU , with more than 200 clinics and arapidly growing community of happy patients.
Our data team plays a key role in powering clinical operations, marketing intelligence, and businessstrategy by building reliable, scalable, and high-quality data pipelines and models.
We are looking for a strong Data Engineer to join our Data Team . You’ll work on core data infrastructure, support large-scale data initiatives, and help build a robust, reliable, and future-proof data ecosystem as we scale globally.
You should be experienced with modern data engineering tools, comfortable working with diverse storage systems and formats, and capable of applying software engineering best practices.
Key Projects You Will Work On
Collecting richer patient data to support marketing optimization and personalization.
Call center and chat automation , as well as improving quality and analytics for communication channels.
Improving overall data quality , observability, lineage, and reliability across datasets. Migrating from Redshift to ClickHouse to improve performance, scalability, and cost efficiency.
Our modern data platform is built on:
DBT (data modeling and transformation)
Airflow (orchestration)
Redshift → ClickHouse (DWH migration in progress)
Parquet, JSON, CSV , and more
Data Pipeline Development
Design, build, and maintain reliable data pipelines using Airflow, DBT, and AWS services.
Ensure pipelines are modular, testable, and follow best software engineering practices.
Implement unit tests, integration tests, and data validations for ETL/ELT workflows.
Data Architecture & Warehousing
Contribute to the Redshift-to-ClickHouse migration , optimizing schema design, storage formats, and query performance.
Evaluate and optimize data storage across structured and semi-structured formats. Ensure data models are stable, efficient, and maintainable.
Data Quality & Observability
Implement and improve data quality checks, automated validations, and anomaly detection. Contribute to data lineage, documentation, and metadata management.
Work closely with Marketing, Product, Engineering, and Operations teams to collect and deliver high-quality data.
Translate business needs into scalable and cost-efficient data solutions.
Support data consumers with access, tooling, and best practices.
5+ years of experience as a Data Engineer working on large-scale data platforms. Strong experience with DBT , Airflow , and cloud environments (preferably AWS ).
Deep understanding of data warehouse technologies , ideally Redshift and/or ClickHouse. Strong knowledge of data storage formats (Parquet, JSON, CSV) and distributed data patterns. Solid software engineering fundamentals:
Writing clean, maintainable code
Version control
Automated testing for pipelines
Strong SQL skills and experience optimizing queries.
Familiarity with Python for ETL, orchestration, or tooling.
Understanding of data governance, access control, and security.
Experience supporting data for marketing automation and CRM systems.
Knowledge of event-driven data processing and streaming.
Opportunity to work on critical, high-impact data systems across multiple regions. A modern data stack.
Work fully remotely, or in our central Barcelona HQ
We operate across three major regions — the US, UK, and EU , with more than 200 clinics and arapidly growing community of happy patients.
Our data team plays a key role in powering clinical operations, marketing intelligence, and businessstrategy by building reliable, scalable, and high-quality data pipelines and models.
We are looking for a strong Data Engineer to join our Data Team . You’ll work on core data infrastructure, support large-scale data initiatives, and help build a robust, reliable, and future-proof data ecosystem as we scale globally.
You should be experienced with modern data engineering tools, comfortable working with diverse storage systems and formats, and capable of applying software engineering best practices.
Key Projects You Will Work On
Collecting richer patient data to support marketing optimization and personalization.
Call center and chat automation , as well as improving quality and analytics for communication channels.
Improving overall data quality , observability, lineage, and reliability across datasets. Migrating from Redshift to ClickHouse to improve performance, scalability, and cost efficiency.
Our modern data platform is built on:
DBT (data modeling and transformation)
Airflow (orchestration)
Redshift → ClickHouse (DWH migration in progress)
Parquet, JSON, CSV , and more
Data Pipeline Development
Design, build, and maintain reliable data pipelines using Airflow, DBT, and AWS services.
Ensure pipelines are modular, testable, and follow best software engineering practices.
Implement unit tests, integration tests, and data validations for ETL/ELT workflows.
Data Architecture & Warehousing
Contribute to the Redshift-to-ClickHouse migration , optimizing schema design, storage formats, and query performance.
Evaluate and optimize data storage across structured and semi-structured formats. Ensure data models are stable, efficient, and maintainable.
Data Quality & Observability
Implement and improve data quality checks, automated validations, and anomaly detection. Contribute to data lineage, documentation, and metadata management.
Work closely with Marketing, Product, Engineering, and Operations teams to collect and deliver high-quality data.
Translate business needs into scalable and cost-efficient data solutions.
Support data consumers with access, tooling, and best practices.
5+ years of experience as a Data Engineer working on large-scale data platforms. Strong experience with DBT , Airflow , and cloud environments (preferably AWS ).
Deep understanding of data warehouse technologies , ideally Redshift and/or ClickHouse. Strong knowledge of data storage formats (Parquet, JSON, CSV) and distributed data patterns. Solid software engineering fundamentals:
Writing clean, maintainable code
Version control
Automated testing for pipelines
Strong SQL skills and experience optimizing queries.
Familiarity with Python for ETL, orchestration, or tooling.
Understanding of data governance, access control, and security.
Experience supporting data for marketing automation and CRM systems.
Knowledge of event-driven data processing and streaming.
Opportunity to work on critical, high-impact data systems across multiple regions. A modern data stack.
Work fully remotely, or in our central Barcelona HQ
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