Senior Data Engineer building and scaling the Databricks/AWS data platform of a fast-growing Barcelona fintech that offers working-capital and invoice-advance solutions. Day to day: design reliable data pipelines with Python/PySpark and dbt, enable AI/ML use cases, optimize cloud storage and performance, and set engineering standards while mentoring the data team.
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Our partner is a rapidly expanding fintech firm based in Barcelona, focused on providing flexible working capital and invoice advance solutions for businesses and entrepreneurs throughout Spain. With an ambitious growth trajectory, the company is positioning itself to become one of the leading players in the sector and aims to achieve unicorn status by 2029.
Mission:
As a Senior Data Engineer, your mission will be to build and evolve the data platform that powers critical business decisions, advanced analytics, and AI-driven products.
You will combine hands-on technical execution, helping define architecture, establish engineering best practices, and support the growth of the wider Data team.
This is a highly strategic role with direct impact on the company's ability to scale its data and AI capabilities.
The Role:
You will work within a modern cloud-based data ecosystem built around Databricks, AWS, and modern data engineering practices.
Your responsibilities will include:
Participating in key decisions regarding the architecture and evolution of the data platform.
Designing and building scalable, reliable, and efficient data pipelines.
Enabling new Artificial Intelligence and Machine Learning use cases in production environments.
Driving technical initiatives and contributing to the growth and maturity of the Data function.
Optimizing data storage, processing, and performance within cloud environments.
Ensuring high standards of data quality, governance, observability, and security.
Collaborating closely with Product, Engineering, Data, and Business stakeholders.
Supporting AI and ML initiatives through the creation of datasets, feature stores, monitoring, and platform capabilities.
Defining engineering standards, deployment practices, and technical documentation.
Providing mentorship through architecture reviews, code reviews, and technical guidance.
What we need:
5+ years of experience in Data Engineering.
Proven experience building and scaling modern data platforms and data pipelines.
Strong expertise in Python and PySpark.
Hands-on experience working with Databricks in production environments.
Experience with Medallion Architecture and modern data platform concepts.
Understanding of Data Mesh principles, domain ownership models, and data products.
Experience working with AWS cloud environments.
Experience using Terraform and Infrastructure as Code practices.
Strong knowledge of dbt for data transformation and modelling.
Solid understanding of data governance, quality, observability, and reliability.
Experience leading technical initiatives and collaborating with multidisciplinary teams.
A mindset focused on business impact, ownership, and continuous improvement.
Nice to Have
Experience supporting AI and Machine Learning products in production.
Knowledge of MLOps tools and practices.
Experience with streaming or near real-time data architectures.
Cloud, Data, or Databricks certifications.
Previous experience in fintech, SaaS, or other high-growth technology environments.
What we offer:
Join a high-growth technology company at a pivotal stage of its journey.
Build the core infrastructure and platform capabilities that will support future growth.
Work on complex technical challenges with direct business impact.
Flexible hybrid working model with remote options depending on location.
Permanent contract.
Flexible working hours.
Private health insurance.
Flexible benefits package.
Regular team events and company offsites. xbhjioe
Strong opportunities for career growth and professional development.