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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** PSI Systems, Inc. - **Location:** Madrid, Spain - **Salary:** €43,000.0 - €52,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Big Data, Code Review, Continuous Delivery, Continuous Integration, Information Engineering, Data Infrastructure, Relational Databases, Python (Programming Language), Machine Learning, Power BI, Software Tools, Standard Sql, Software Construction, SQL Databases, Tableau (Software), Data Processing, Large Language Models, Apache Spark, Data Strategy, Cloudformation, Integration Frameworks, Terraform, Looker Analytics, Software Version Control, Data Pipelines, Unsupervised Learning, Databricks - **Published:** August 29, 2026 - **Apply:** https://job-boards.greenhouse.io/auctane/jobs/7977912003 ## About the Role * Experience developing and supporting robust, automated, and reliable data pipelines in Python and SQL. * Mastered Python and SQL skills. * Experience with data processing frameworks like Spark or dbt. * Knowledge of Data Orchestration solutions, like Databricks Lakeflow or Airflow. * Knowledge of relational database design * A desire to constantly challenge the norm, with a proven track record of promoting and maintaining high engineering standards. * Fast learner with a keen interest in evaluating and adopting new technologies. What will make you stand out? * Production experience working with very large datasets. * Direct experience with Infrastructure as Code tools (e.g., Terraform, CloudFormation) * Knowledge and direct experience in using business intelligence and analytics tools (Tableau, Looker, Power BI, etc.) * Understanding of core ML concepts like supervised and unsupervised learning, overfitting, and cross-validation as well as LLM concepts like fine-tuning, etc. * Comfortable working with AI-assisted engineering tools (e.g., Claude Code) to accelerate development and code review. The tech stack * Databricks * Python * SQL * Spark ## Description In this role, you will have an impact on the design, implementation, and maintenance of existing and greenfield customer-facing and internal data products. We work at a scale pace and with the latest architecture patterns and tech. We process thousands of events per second, and our massive dataset keeps growing at a staggering pace. We keep improving our data platform and data engineering stack to accommodate growth, enable novel solutions, and provide the best service to our customers. We have a flat and open engineering culture where data & evidence beat opinion and hierarchy, backed by honest discussions. We passionately believe in forming autonomous, cross-functional teams who are empowered to deliver our ambitious strategy. Energy and passion for our business and customers are part of our culture - and we love working with like-minded people. This role is based in Madrid, Spain What will you be doing? * Contribute to the design, build, and operational management of our data pipelines and analytics solution using Databricks. * Collaborate with the Product Owner and other stakeholders to implement the ShipStation Global data strategy. * Develop frameworks and solutions that enable us to acquire, process, monitor and extract value from our enterprise-wide dataset. * Contribute to the design and architecture of ShipStation Global's data platform. * Contribute directly to the implementation and operations of our systems. * Be an advocate of data quality and observability principles and use Databricks Lakeflow and Spark to process data and get our datasets just right. * Foster engineering excellence by delivering highly reliable software and data pipelines using Software Engineering best practices like automation, version control, continuous integration/continuous delivery, testing, security, etc. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)