Help design, build and continuously improve the clients online platform.
Research, suggest and implement new technology solutions following best practices/standards.
Take responsibility for the resiliency and availability of different products.
Be a productive member of the team.

Requirements

Experienced Data Engineer with deep expertise in Azure Databricks, Python/PySpark, and SQL, focused on building robust, scalable, and reliable data processing solutions within the Databricks ecosystem.
The role emphasizes data processing and engineering rather than data enrichment or traditional BI architectures.
Strong hands-on expertise in Azure Databricks as the core technology.
Deep proficiency in Python, PySpark, and SQL.
Proven experience designing and managing data processing solutions in Databricks.
Strong experience with both batch and streaming data processing.
Experience designing and implementing effective data models within Databricks.
Ability to manage multiple parallel data processing workloads using shared source data.
Strong knowledge of Azure cloud services and CI/CD pipelines using YAML.
Hands-on experience with Infrastructure as Code (IaC) using ARM Templates/Bicep.
Experience working in an Agile environment.
Good understanding of end-to-end data engineering and data platform solutions.
Strong focus on quality, reliability, scalability, and maintainability, with an emphasis on minimizing technical debt.
Proactive approach to continuous improvement and problem-solving.
Strong communication and collaboration skills.
Structured, pragmatic, and solution-oriented approach to engineering.
Ability to avoid over-engineering and apply design patterns appropriately based on actual requirements.

Benefits

Fixed Term Employment Contract
Work-Life Balance
Flexible Work Mode

What GeekSoft Consulting Offers

International, collaborative consulting culture with clear career development paths.
Comprehensive Dutch benefits package emphasizing well-being, mobility, and career growth.

المهارات المطلوبة

Azure DatabricksPython / PySparkSQLBatch and streaming data processingData modeling within DatabricksDesigning and managing data processing solutions in DatabricksManaging multiple parallel data processing workloads with shared source dataAzure cloud servicesCI/CD pipelines using YAMLInfrastructure as Code (ARM Templates / Bicep)End-to-end data engineering and data platform architecturePragmatic solution design and application of design patterns (avoid over-engineering)Communication and collaboration skills

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