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Senior Data Engineer – Cloud Data Platform

Bekijk en reageer bij levy-professionals.com (externe link)

Senior Data Engineer for a modern cloud data platform (Azure Databricks, PySpark, Python, SQL) in Amsterdam, North Holland.

Locatie
Amsterdam
Werkvorm
hybride
Contractvorm
detachering
Eerste waarneming
Opdrachtgever
Levy Professionals

Eisen

Wensen

Omschrijving

We are looking for a Senior Data Engineer to join an Agile Data Engineering team and help build and evolve a modern, cloud-based data platform. You will design, develop, and operate scalable data solutions that support critical business processes and enable data-driven decision-making. Key responsibilities include designing, developing, and maintaining scalable data pipelines and data products using Azure Databricks, PySpark, Python, and SQL; building and optimizing data ingestion, transformation, and storage solutions for analytics, reporting, and operational use cases; developing and supporting ETL/ELT processes integrating data from multiple sources into trusted and governed data platforms; designing and reviewing cloud-native solutions leveraging Azure Data Lake Storage (ADLS), Azure Functions, Databricks, and Apache Airflow; ensuring data quality, reliability, scalability, monitoring, and operational excellence across the data ecosystem; implementing and maintaining source control, CI/CD pipelines, and deployment automation using Azure DevOps; collaborating with business and technical stakeholders to translate requirements into robust and sustainable solutions; enhancing existing data products, optimizing platform capabilities, and continuously improving engineering practices; troubleshooting and resolving complex production issues using strong analytical and problem-solving skills; contributing to data architecture, engineering standards, and best practices across the organization; promoting innovation, knowledge sharing, and continuous improvement within the Data Engineering community; and championing Agile, DevOps, and DataOps principles as part of a cross-functional Scrum team. The working environment is an Agile DevOps team within a Data Engineering organization, collaborating with colleagues across engineering and business functions to analyze, design, develop, test, deploy, and support secure, scalable, and future-proof data solutions. The profile requires 5+ years of experience in Data Engineering, preferably on cloud-based data platforms; strong hands-on experience with Azure Databricks, including Unity Catalog and Databricks Asset Bundles (DAB); hands-on experience with Apache Airflow, ADLS, and Azure Functions; strong proficiency in Python (OOP), PySpark, and SQL; solid understanding of Apache Spark performance tuning and large-scale data processing; experience building and maintaining ETL/ELT pipelines and modern data integration solutions; experience with Git, CI/CD, and Azure DevOps; knowledge of data modelling techniques, including dimensional modelling; strong analytical, troubleshooting, and communication skills; and experience working in Agile/Scrum and DevOps environments. Nice to have: experience with monitoring, observability, logging, and data lineage; familiarity with Delta Lake, Iceberg, or other modern data lake technologies; knowledge of data governance, metadata management, and data quality frameworks; Azure and/or Databricks certifications; and experience in Financial Services or other highly regulated environments. What you can expect: the opportunity to work on a modern cloud data platform at scale, a collaborative Agile environment with strong engineering and data practices, the opportunity to contribute to architecture, standards, and continuous improvement, and a role combining hands-on engineering with opportunities to influence how data solutions are designed and delivered.

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