Senior Data Engineer

Qualifyze; Barcelona; On-site; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Truly flexible schedules

Regular company events

A selection of free drinks at the офис

Mentoring and career development

The hotel room is your office - work从另

Flexible compensation plan - Edenred /

Job summary

Qualifyze is seeking a Senior Data Engineer to join our Product & Tech team in Barcelona. You will design, build, and maintain scalable data pipelines and data products, owning end-to-end data features from ingestion to analytics delivery.

You will collaborate with product and backend engineers, stakeholders, and cross-functional teams to translate requirements into well-scoped data solutions, while improving data quality and observability across the platform.

Qualifications

• Strong data modeling skills including dimensional modeling
• Excellent SQL skills and PostgreSQL experience
• Proficiency in Python for ETL/ELT workflows with strong tests and observability
• Experience with data platforms, pipelines, and data products
• Knowledge of data orchestration tools (Dagster or Airflow)

Responsibilities

• Design, build, and maintain scalable data pipelines and products
• Own end-to-end data features from ingestion to analytics delivery
• Collaborate with product and backend engineers to translate requirements
• Improve data quality, testing, and code review standards
• Monitor pipelines, troubleshoot incidents, and enhance observability

Tools

PostgreSQL

Python

Dagster

Airflow

dbt

Liquibase

AWS

Spark

Data Modeling

Docker

Kubernetes

Job description

• We are looking for a Senior Data Engineer to join our growing Product & Tech team. In this role, you will help build and evolve our data platform, owning key pipelines and data products from end to end and contributing to the engineering decisions that shape them


• Your main goal will be to design, build, and maintain reliable data pipelines across our operational databases and analytical platform, applying quality software engineering practices to everything you ship


• You will collaborate closely with the product team and backend engineers, and work directly with business stakeholders who depend on accurate, timely data to drive product decisions


• Design, build, and maintain scalable, reliable, and well-tested data pipelines and data products


• Manage features and pipelines end-to-end: from schema design in operational databases through ingestion, transformation, and delivery of analytical datasets


• Contribute to the architecture of our data platform and help evaluate technical trade-offs with the team


• Apply and help improve standards for data modeling, data quality, testing, and code review


• Work with Product, Engineering, and business stakeholders to turn requirements into well-scoped data solutions


• Monitor, troubleshoot, and resolve pipeline incidents, and improve observability and reliability over time


• Share knowledge with the team and mentor fellow engineers through pairing and code reviews

Benefits

• Truly flexible schedules


• Regular company events


• A selection of free drinks at the office


• Mentoring and career development


• The hotel room is your office - we allow working from another country up to 3 months a year


• Flexible compensation plan - our Edenred and become.1 cards are an open door to customisable benefits and tax savings

Solid grasp of data modeling, including dimensional modeling and the trade-offs between operational and analytical schemasStrong SQL skills with PostgreSQL, including complex query design, performance tuning, indexing, and reading execution plans for both OLTP and OLAP workloadsProficiency in Python for data engineering, including building robust ETL/ELT pipelines and reusable modules, with strong testing and good observabilityWorking knowledge of Docker and Kubernetes, including packaging and running data services and batch jobs in productionExperience with Dagster or similar orchestrators such as Airflow, including building assets/jobs, scheduling, monitoring, and handling failures in production workflowsHands-on experience with dbt, building, testing, and documenting models, ideally in a layered project structureExperience with database schema migration tools (such as Liquibase) or data contractsExperience with AWS (S3, EKS, Secrets Manager)