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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Valona Intelligence - **Location:** Amsterdam, Netherlands - **Experience:** Expert - **Salary:** €4,500.0 - €4,958.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Application Performance Management, Application Services, Microsoft Azure, Cloud Computing, Code Review, Data Infrastructure, Relational Databases, Software Debugging, Software Design Patterns, Python (Programming Language), Microsoft SQL Server, Raw Data, Power BI, Standard Sql, Selenium, SQL Stored Procedures, SQL Databases, Unstructured Data, Data Ingestion, Microsoft Power Automate, Apache Spark, Indexer, Git, Pandas, Pyspark, Maintaining Code, Graphql, SQL Server Management Studio (SSMS), Data Pipelines, Docker - **Published:** September 4, 2026 - **Apply:** https://www.adzuna.nl/details/5869273615 ## About the Role * 2 to 4 years of experience as a data engineer, with experience in both Python and SQL. * Experience developing and maintaining code that runs in production. * Good SQL skills: you can write and optimize queries against a relational database, ideally SQL Server. * Experience with Azure (or other cloud infrastructure). * Experienced in using Git and Git workflow * A good understanding of clean code, common design patterns, and debugging. * Comfortable working with data: data quality rules, different formats, transformations, and matching records between sources. * Experienced with development in popular IDE tooling's, preferably VS Code * Interested in using AI tools to work faster, not only in building AI features. ## Description You help run our data platform: getting data in, validating, cleaning and transforming it into clean tables, and making it available to the rest of the company. You also help us use AI in this work. * Collect structured and unstructured data with Python scrapers and API connectors. * Handle the first steps of our ELT process: validation, normalization, schema mapping, and entity mapping (matching the same company, product, or source across different datasets), so other teams get clean, reliable tables. * Write and improve SQL that turns raw data into clean staging and processed tables. This is a mix of Python and SQL work, moving between the two as needed. You also write stored procedures, and follow best practices for schema design, indexing, and storage. * Be the primary developer of one or more dataflows end-to-end, from ingestion all the way to the API that exposes the data to other teams and systems. * Debug and fix problems fast, using logs, metrics, and alerts. * Review code, write tests, and keep the codebase clean. Improve each part of the system you touch. * Use AI tools daily to help you code (for example Claude Code). Connect your data to the AI agents our AI team builds in Microsoft Foundry, by exposing clean, well-structured data and APIs they can use. Projects in your first year * Add new types of data as the business grows, for example patent data or financial data. * Improve our tools for matching public data to our own records. * Help the business with data quality, such as fix mappings, updating records, or making manual changes when needed. Ongoing work * Build and maintain Python ingestion jobs and SQL-based ELT pipelines, moving between the two as the work needs. Keep the pipelines simple, modular, and easy to monitor. * Development and maintenance of our CI/CD pipelines and follow the internal workflow * Monitor data pipelines in Azure and via Power BI. * Help keep the data platform reliable, scalable, and secure. * Follow and expand on good practices for design, testing, and documentation. * Build and maintain the Azure infrastructure needed for data ingestion and transformation. * Use AI tools where they help, from coding assistants to connecting our data to the agents our AI team builds. Tools you'll use every day * Python (including Pandas, Selenium, and our internal libraries) * SQL (SQL Server Management Studio) * API integration (REST, GraphQL) * Azure DevOps (CI/CD pipelines) * Git * Docker and Azure Container Registry * Azure Function App and Azure Durable Function * Azure Logic App * AI coding tools, such as Claude Code Tools you'll also use * Microsoft Foundry (formerly Azure AI Foundry) * Azure App Services * Fabric * Spark including PySpark * Azure Storage (Blob, Table, Queue) * Azure Monitor / Application Insights ## 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) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Getting to Know Your Legacy (System) with AI-Driven Software Archeology](https://www.wearedevelopers.com/videos/1437-getting-to-know-your-legacy-system-with-ai-driven-software-archeology) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)