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
- 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
- Hands-on experience with Apache Airflow, ADLS, and Azure Functions
- Knowledge of data modelling techniques, including dimensional modelling
- Strong analytical, troubleshooting, and communication skills
- Experience with Git, CI/CD, and Azure DevOps
- Experience working in Agile/Scrum and DevOps environments
- Strong hands-on experience with Azure Databricks, including Unity Catalog and Databricks Asset Bundles (DAB)
- 5+ years of experience in Data Engineering, preferably on cloud-based data platforms
Wensen
- Knowledge of data governance, metadata management, and data quality frameworks
- Experience in Financial Services or other highly regulated environments
- Familiarity with Delta Lake, Iceberg, or other modern data lake technologies
- Azure and/or Databricks certifications
- Experience with monitoring, observability, logging, and data lineage
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.
Alle opdrachtenBekijk en reageer bij levy-professionals.com (externe link)
Gegevens automatisch overgenomen uit de oorspronkelijke publicatie; controleer de details bij de bron. Wij zijn geen partij bij de aanvraag. Hoe wij werken.