Inhuurbron

Senior Data engineer

Bekijk en reageer bij IQ Staffing (externe link)

Senior Data Engineer (Azure Databricks) voor een financiële instelling in Amsterdam, hybride, via detachering.

Locatie
Amsterdam
Werkvorm
hybride
Contractvorm
detachering
Eerste waarneming
Opdrachtgever
leading financial institution in Amsterdam

Eisen

Wensen

Omschrijving

Help build and improve a cloud-based data platform that supports critical transaction banking processes at a leading financial institution. For our client, a leading financial institution in Amsterdam, you will join the Transaction Banking Domain Data Store team, working on scalable data products used for analytics, reporting and operational decision-making. This is a hands-on engineering role with room to influence architecture, standards and the way data solutions are built and operated. What you will do: Design and maintain scalable data pipelines using Azure Databricks, PySpark, Python and SQL. Build ingestion, transformation and storage solutions for large volumes of data. Develop reliable ETL and ELT pipelines connecting multiple source systems. Work with Azure Data Lake Storage, Azure Functions, Databricks and Apache Airflow. Improve data quality, monitoring, reliability and platform performance. Automate testing and deployments through Azure DevOps and CI/CD. Troubleshoot complex production issues and implement sustainable solutions. Translate business requirements into robust data products. Contribute to data architecture, engineering standards and best practices. Share knowledge and improve engineering practices within the wider Data Engineering community. Key projects include the Infinity Flow migration, alignment with the Data Quality Framework and the development of a Surrogate Key Generator. What you bring: Strong hands-on experience with Azure Databricks, including Unity Catalog and Databricks Asset Bundles. Experience with Apache Airflow, ADLS and Azure Functions. Strong Python skills, including object-oriented programming. Solid experience with PySpark and SQL. Knowledge of Spark performance tuning and large-scale data processing. Experience building and maintaining ETL/ELT pipelines. Experience with Git, CI/CD and Azure DevOps. Knowledge of dimensional data modelling. Strong analytical and troubleshooting skills. Experience working in Agile, Scrum, DevOps or DataOps environments. Clear communication skills and the ability to work with both technical and business stakeholders. Nice to have: Experience with monitoring, observability, logging and data lineage. Knowledge of Delta Lake, Iceberg or similar data lake technologies. Experience with data governance, metadata management or data quality frameworks. Azure or Databricks certifications. Experience in financial services or transaction banking. Exposure to Agentic AI. Working arrangement: You will work in a hybrid setup, with two days per week at the office. This position is offered through a secondment arrangement.

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