Staff Data Engineer

Qualifyze; Barcelona; Presencial; EUR 90.000 - 130.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Truly flexible schedules

Regular company events

Free drinks at the office

Mentoring and career development

Work from abroad up to 3 months/year

Flexible compensation plan

Descripción de la vacante

Qualifyze in Barcelona seeks a Staff Data Engineer to shape the data platform, partnering with Product and Backend teams to design scalable data architectures.

You will own end-to-end data pipelines, modeling, quality and performance, and mentor other Data Engineers while driving best practices across SQL, Python, dbt and orchestration tools.

The role offers flexible schedules, company events, and options to work from abroad for up to three months a year.

Formación

• Strong skills in Python and SQL with production data experience.
• End-to-end data pipelines across operational and analytical data.
• Experience with dbt, and orchestration tools like Dagster.
• Hands-on with containerization (Docker) and Kubernetes.
• Solid data modeling and data quality practices.

Responsabilidades

• Define and drive the technical vision for the data platform and architecture.
• Design scalable, reliable data solutions and maintainable pipelines.
• Mentor Data Engineers and promote best practices across teams.
• Collaborate with Product and Backend to translate business needs into data products.
• Improve data quality, observability, and performance across systems.

Conocimientos

Python

SQL

Data engineering

End-to-end pipelines

Mentoring

Herramientas

dbt

Dagster

Docker

Kubernetes

PostgreSQL

Descripción del empleo

• We are looking for a Staff Data Engineer to join our growing Product & Tech team. In this role, you will help shape the evolution of our data platform and influence engineering decisions across multiple cross-functional teams
• Your main goal will be to partner with us in designing and scaling our data platform, strengthening both our operational databases and analytical platform, and bringing quality software engineering practices to all our data products and pipelines
• You’ll collaborate closely with the product team and backend engineers, and serve as a trusted partner to business stakeholders who depend on accurate, timely data to drive product decisions and company strategy
• Define and drive the technical vision for our data platform and architecture
• Design scalable, reliable, and maintainable data solutions that support business growth
• Establish and cultivate best practices around data architecture, modeling, quality, and engineering standards
• Lead complex technical initiatives and make strategic architectural decisions across multiple teams
• Partner with Product, Engineering, and business stakeholders to translate business needs into scalable data solutions
• Mentor and support Data Engineers, fostering technical growth and knowledge sharing across the team
• Drive continuous improvements that increase the scalability, reliability, and efficiency of our data platform

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

This role is ideal for someone with strong skills in Python and SQL, solid software engineering fundamentals, a background in data-intensive product or platform teams where they contributed to production data architectures and pipelines end to end, and the ability to succeed in a dynamic, outcome-focused environment owning the full data cycle from operational to analytical systemsAdvanced SQL skills with PostgreSQL: Complex query design, performance tuning, indexing strategies, and a deep understanding of execution plans for both OLTP and OLAP workloadsStrong experience with dbt: Data modeling, testing, and documenting analytical datasets, managing environments, and structuring projects for scalabilityStrong grasp of data modeling: Dimensional modeling plus a clear understanding of trade-offs for operational vs analytical schemasHands-on experience with Dagster (or similar orchestration tools): Designing assets/jobs, dependency graphs, scheduling, monitoring, and incident handling for data workflowsProficiency in Python for data engineering: Building robust ETL/ELT pipelines, modular libraries, and tooling with strong testing and observabilitySolid knowledge of containerization and orchestration: Docker and Kubernetes for deploying data services, batch jobs, and microservices in production