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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - Analyst - **Company:** LEVY PROFESSIONALS - **Location:** Den Haag, Netherlands - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Airflow, Microsoft Azure, BigQuery, Cloud Database, Continuous Integration, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Python (Programming Language), Reference Data, SQL Databases, System Availability, Snowflake, Data Management, Data Pipelines - **Published:** July 9, 2026 - **Apply:** https://nl.indeed.com/viewjob?jk=d4fdc8159aa9b642 ## About the Role * At least 5 years of experience as a Data Engineer within a financial institution. * Strong experience with SQL and Python. * Hands-on experience with dbt and Apache Airflow. * Experience with cloud data warehouse technologies such as Snowflake, BigQuery, or Redshift. * Experience with Azure and CI/CD practices is an advantage. * Strong understanding of data modelling, ETL development, and data quality principles. * Experience working with financial and investment data such as portfolios, transactions, market data, pricing, or reference data. * Good understanding of financial products and investment processes within asset management, banking, or another financial services environment. * Familiarity with data governance and working in regulated environments. * Strong analytical and problem-solving skills with great attention to detail. * Excellent communication skills in English. * Comfortable working with both technical teams and business stakeholders. ## Description Are you an experienced Data Engineer with a background in the financial sector? Do you enjoy building reliable data platforms that support critical investment and business processes? Join an international organisation where you'll work with modern cloud technologies, help improve data quality, and play a key role in delivering trusted data for finance professionals and business stakeholders. About the role As a Data Engineer, you will design, build, and maintain scalable data pipelines that power business-critical applications across a complex financial environment. Working closely with both IT and business teams, you will ensure data is accurate, consistent, and available for reporting, analytics, and operational processes. You will be working with a wide range of financial and investment data, including portfolios, transactions, valuations, market data, and reference data. An understanding of investment management processes, financial products, and the importance of high-quality data within a regulated environment will help you succeed in this role. Your responsibilities include: * Designing, developing, and maintaining modern data pipelines and ETL processes. * Building and optimising data models within a cloud-based data warehouse. * Developing data transformations using dbt and orchestrating workflows with Apache Airflow. * Ensuring high standards of data quality, governance, monitoring, and documentation. * Collaborating with business and IT stakeholders to translate functional requirements into scalable data solutions. * Supporting data availability for reporting, analytics, and business decision-making. * Driving continuous improvements across the data platform and engineering practices. This is a long-term project within a highly collaborative environment where data is at the heart of business operations and investment decision-making. ## 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) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Making Data Warehouses fast. 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